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1.  Associations between tooth loss and mortality patterns in the Glasgow Alumni Cohort 
Heart  2006;93(9):1098-1103.
To use data from the Glasgow Alumni Cohort to investigate whether oral health in young adulthood is independently associated with later life cardiovascular disease (CVD) and cancer mortality.
Methods and results
Of the original cohort (n = 15 322), 12 631 subjects were traced through the National Health Service Central Register. Of these, 9569 men and 2654 women were 30 years or younger at baseline. During up to 57 years of follow‐up, 1432 deaths occurred among subjects with complete data, including 509 deaths from CVD and 549 from cancer. After adjusting for potential confounders, no substantial association was found between the number of missing teeth (as a continuous variable) and all‐cause mortality (hazard ratio (HR) for each extra missing tooth  = 1.01; 95% confidence interval (CI) 1.00 to 1.02), CVD mortality (HR = 1.01; 95% CI 0.99 to 1.03) or cancer mortality (HR = 1.00; 95% CI 0.98 to 1.02). When the number of missing teeth was treated as a categorical variable, there was evidence that students with nine or more missing teeth at baseline had an increased risk of CVD (HR = 1.35; 95% CI 1.03 to 1.77) compared with those with fewer than five missing teeth. When the number of missing teeth was transformed using fractional polynomials, there seemed to be a non‐linear relation between missing teeth and CVD mortality.
Although some evidence was found to support the relation between tooth loss and CVD mortality, causal mechanisms underlying this association remain uncertain.
PMCID: PMC1955024  PMID: 17164486
tooth loss; cardiovascular diseases; stroke; coronary heart diseases; mortality
2.  A Primer on Network Meta-Analysis for Dental Research 
ISRN Dentistry  2012;2012:276520.
In the last decade, a new statistical methodology, namely, network meta-analysis, has been developed to address limitations in traditional pairwise meta-analysis. Network meta-analysis incorporates all available evidence into a general statistical framework for comparisons of all available treatments. A further development in the network meta-analysis is to use a Bayesian statistical approach, which provides a more flexible modelling framework to take into account heterogeneity in the evidence and complexity in the data structure. The aim of this paper is therefore to provide a nontechnical introduction to network meta-analysis for dental research community and raise the awareness of it. An example was used to demonstrate how to conduct a network meta-analysis and the differences between it and traditional meta-analysis. The statistical theory behind network meta-analysis is nevertheless complex, so we strongly encourage close collaboration between dental researchers and experienced statisticians when planning and conducting a network meta-analysis. The use of more sophisticated statistical approaches such as network meta-analysis will improve the efficiency in comparing the effectiveness between multiple treatments across a set of trials.
PMCID: PMC3418651  PMID: 22919506
3.  A Prospective Study of Growth and Biomarkers of Exposure to Aflatoxin and Fumonisin during Early Childhood in Tanzania 
Environmental Health Perspectives  2014;123(2):173-178.
Background: Aflatoxin and fumonisin are toxic food contaminants. Knowledge about effects of their exposure and coexposure on child growth is inadequate.
Objective: We investigated the association between child growth and aflatoxin and fumonisin exposure in Tanzania.
Methods: A total of 166 children were recruited at 6–14 months of age and studied at recruitment, and at the 6th and 12th month following recruitment. Blood and urine samples were collected and analyzed for plasma aflatoxin–albumin adducts (AF-alb) using ELISA, and urinary fumonisin B1 (UFB1) using liquid chromatography–mass spectrometry, respectively. Anthropometric measurements were taken, and growth index z-scores were computed.
Results: AF-alb geometric mean concentrations (95% CIs) were 4.7 (3.9, 5.6), 12.9 (9.9, 16.7), and 23.5 (19.9, 27.7) pg/mg albumin at recruitment, 6 months, and 12 months from recruitment, respectively. At these respective sampling times, geometric mean UFB1 concentrations (95% CI) were 313.9 (257.4, 382.9), 167.3 (135.4, 206.7), and 569.5 (464.5, 698.2) pg/mL urine, and the prevalence of stunted children was 44%, 55%, and 56%, respectively. UFB1 concentrations at recruitment were negatively associated with length-for-age z-scores (LAZ) at 6 months (p = 0.016) and at 12 months from recruitment (p = 0.014). The mean UFB1 of the three sampling times (at recruitment and at 6 and 12 months from recruitment) in each child was negatively associated with LAZ (p < 0.001) and length velocity (p = 0.004) at 12 months from recruitment. The negative association between AF-alb and child growth did not reach statistical significance.
Conclusions: Exposure to fumonisin alone or coexposure with aflatoxins may contribute to child growth impairment.
Citation: Shirima CP, Kimanya ME, Routledge MN, Srey C, Kinabo JL, Humpf HU, Wild CP, Tu YK, Gong YY. 2015. A prospective study of growth and biomarkers of exposure to aflatoxin and fumonisin during early childhood in Tanzania. Environ Health Perspect 123:173–178;
PMCID: PMC4314247  PMID: 25325363
4.  Comparative effectiveness of renin-angiotensin system blockers and other antihypertensive drugs in patients with diabetes: systematic review and bayesian network meta-analysis 
Objective To assess the effects of different classes of antihypertensive treatments, including monotherapy and combination therapy, on survival and major renal outcomes in patients with diabetes.
Design Systematic review and bayesian network meta-analysis of randomised clinical trials.
Data sources Electronic literature search of PubMed, Medline, Scopus, and the Cochrane Library for studies published up to December 2011.
Study selection Randomised clinical trials of antihypertensive therapy (angiotensin converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), α blockers, β blockers, calcium channel blockers, diuretics, and their combinations) in patients with diabetes with a follow-up of at least 12 months, reporting all cause mortality, requirement for dialysis, or doubling of serum creatinine levels.
Data extraction Bayesian network meta-analysis combined direct and indirect evidence to estimate the relative effects between treatments as well as the probabilities of ranking for treatments based on their protective effects.
Results 63 trials with 36 917 participants were identified, including 2400 deaths, 766 patients who required dialysis, and 1099 patients whose serum creatinine level had doubled. Compared with placebo, only ACE inhibitors significantly reduced the doubling of serum creatinine levels (odds ratio 0.58, 95% credible interval 0.32 to 0.90), and only β blockers showed a significant difference in mortality (odds ratio 7.13, 95% credible interval 1.37 to 41.39). Comparisons among all treatments showed no statistical significance in the outcome of dialysis. Although the beneficial effects of ACE inhibitors compared with ARBs did not reach statistical significance, ACE inhibitors consistently showed higher probabilities of being in the superior ranking positions among all three outcomes. Although the protective effect of an ACE inhibitor plus calcium channel blocker compared with placebo was not statistically significant, the treatment ranking identified this combination therapy to have the greatest probability (73.9%) for being the best treatment on reducing mortality, followed by ACE inhibitor plus diuretic (12.5%), ACE inhibitors (2.0%), calcium channel blockers (1.2%), and ARBs (0.4%).
Conclusions Our analyses show the renoprotective effects and superiority of using ACE inhibitors in patients with diabetes, and available evidence is not able to show a better effect for ARBs compared with ACE inhibitors. Considering the cost of drugs, our findings support the use of ACE inhibitors as the first line antihypertensive agent in patients with diabetes. Calcium channel blockers might be the preferred treatment in combination with ACE inhibitors if adequate blood pressure control cannot be achieved by ACE inhibitors alone.
PMCID: PMC3807847  PMID: 24157497
5.  Age-period-cohort analysis for trends in body mass index in Ireland 
BMC Public Health  2013;13:889.
Obesity is a growing problem worldwide and can often result in a variety of negative health outcomes. In this study we aim to apply partial least squares (PLS) methodology to estimate the separate effects of age, period and cohort on the trends in obesity as measured by body mass index (BMI).
Using PLS we will obtain gender specific linear effects of age, period and cohort on obesity. We also explore and model nonlinear relationships of BMI with age, period and cohort. We analysed the results from 7,796 men and 10,220 women collected through the SLAN (Surveys of Lifestyle, attitudes and Nutrition) in Ireland in the years 1998, 2002 and 2007.
PLS analysis revealed a positive period effect over the years. Additionally, men born later tended to have lower BMI (−0.026 kg·m-2 yr-1, 95% CI: -0.030 to −0.024) and older men had in general higher BMI (0.029 kg·m-2 yr-1, 95% CI: 0.026 to 0.033). Similarly for women, those born later had lower BMI (−0.025 kg·m-2 yr-1, 95% CI: -0.029 to −0.022) and older women in general had higher BMI (0.029 kg·m-2 yr-1, 95% CI: 0.025 to 0.033). Nonlinear analyses revealed that BMI has a substantial curvilinear relationship with age, though less so with birth cohort.
We notice a generally positive age and period effect but a slightly negative cohort effect. Knowing this, we have a better understanding of the different risk groups which allows for effective public intervention measures to be designed and targeted for these specific population subgroups.
PMCID: PMC3852547  PMID: 24067048
Obesity; Age-period-cohort; Partial least squares
6.  Stability of the Factor Structure of the Metabolic Syndrome across Pubertal Development: Confirmatory Factor Analyses of Three Alternative Models 
The Journal of pediatrics  2009;155(3):S5.e1-S5.e8.
To test the fit and stability of 3 alternative models of the metabolic syndrome’s factor structure across 3 developmental stages.
Study design
With data from the Fels Longitudinal Study, confirmatory factor analyses tested 3 alternative models of the factor structure underlying relationships among 8 metabolic syndrome-associated risks. Models tested were a 1-factor model (A), a 4-factor model (B), and a second-order latent factor model (C). Developmental stages assessed were prepuberty (ages 8–10), puberty (ages 11–15), and postpuberty (ages 16–20).
Convergence was achieved for all developmental stages for model A, but the fit was poor throughout (root mean square error of approximation > 0.1). Standardized factor loadings for waist circumference and body mass index were much stronger than those for fasting insulin at all 3 time points. Although prepuberty and postpuberty models converged for models B and C, each model had problems with Heywood cases. The puberty model did not converge for either model B or C.
The hypothetical structures commonly used to support the metabolic syndrome concept do not provide adequate fit in a pediatric sample and may be variable by maturation stage. A components-based approach to cardiovascular risk reduction, with emphasis on obesity prevention and control, may be a more appropriate clinical strategy for children and youth than a syndromic approach.
PMCID: PMC3763727  PMID: 19732562
7.  Differential effects of the changes of LDL cholesterol and systolic blood pressure on the risk of carotid artery atherosclerosis 
The effects of baseline and changes in blood pressure and low density lipoprotein (LDL) cholesterol on the carotid intima media thickness (IMT) have not been well documented.
A total of 2572 adults (mean age 53.8 years, 54.6% women) in a Taiwanese community undertook three blood pressure and LDL cholesterol examinations over 6 years. Latent growth curve modeling was used to investigate the effects of baseline and change in blood pressure and LDL cholesterol on IMT.
Greater baseline LDL and blood pressure were associated with an increase in IMT (0.005 ± 0.002 mm per 1 mg/dL [p = 0.006] and 0.041 ± 0.004 mm mmHg [p <0.0001], respectively. Change in blood pressure was associated with a significant increase in IMT (0.047±0.016, P = 0.004), whilst the association between change in LDL and change in IMT was not statistically significant (0.008±0.006, P = 0.20).
Carotid IMT was associated with baseline blood pressure and LDL cholesterol, yet only changes of blood pressure, not LDL cholesterol, were related to carotid IMT during the 6-year observation.
PMCID: PMC3445849  PMID: 22900906
Latent growth curve modeling; Carotid intima media thickness; Blood pressure; LDL cholesterol
8.  A Comparison of Different Approaches to Unravel the Latent Structure within Metabolic Syndrome 
PLoS ONE  2012;7(4):e34410.
Exploratory factor analysis is a commonly used statistical technique in metabolic syndrome research to uncover latent structure amongst metabolic variables. The application of factor analysis requires methodological decisions that reflect the hypothesis of the metabolic syndrome construct. These decisions often raise the complexity of the interpretation from the output. We propose two alternative techniques developed from cluster analysis which can achieve a clinically relevant structure, whilst maintaining intuitive advantages of clustering methodology.
Two advanced techniques of clustering in the VARCLUS and matroid methods are discussed and implemented on a metabolic syndrome data set to analyze the structure of ten metabolic risk factors. The subjects were selected from the normative aging study based in Boston, Massachusetts. The sample included a total of 847 men aged between 21 and 81 years who provided complete data on selected risk factors during the period 1987 to 1991.
Four core components were identified by the clustering methods. These are labelled obesity, lipids, insulin resistance and blood pressure. The exploratory factor analysis with oblique rotation suggested an overlap of the loadings identified on the insulin resistance and obesity factors. The VARCLUS and matroid analyses separated these components and were able to demonstrate associations between individual risk factors.
An oblique rotation can be selected to reflect the clinical concept of a single underlying syndrome, however the results are often difficult to interpret. Factor loadings must be considered along with correlations between the factors. The correlated components produced by the VARCLUS and matroid analyses are not overlapped, which allows for a simpler application of the methodologies and interpretation of the results. These techniques encourage consistency in the interpretation whilst remaining faithful to the construct under study.
PMCID: PMC3317545  PMID: 22485169
9.  Unravelling the effects of age, period and cohort on metabolic syndrome components in a Taiwanese population using partial least squares regression 
We investigate whether the changing environment caused by rapid economic growth yielded differential effects for successive Taiwanese generations on 8 components of metabolic syndrome (MetS): body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting plasma glucose (FPG), triglycerides (TG), high-density lipoprotein (HDL), Low-density lipoproteins (LDL) and uric acid (UA).
To assess the impact of age, birth year and year of examination on MetS components, we used partial least squares regression to analyze data collected by Mei-Jaw clinics in Taiwan in years 1996 and 2006. Confounders, such as the number of years in formal education, alcohol intake, smoking history status, and betel-nut chewing were adjusted for.
As the age of individuals increased, the values of components generally increased except for UA. Men born after 1970 had lower FPG, lower BMI, lower DBP, lower TG, Lower LDL and greater HDL; women born after 1970 had lower BMI, lower DBP, lower TG, Lower LDL and greater HDL and UA. There is a similar pattern between the trend in levels of metabolic syndrome components against birth year of birth and economic growth in Taiwan.
We found cohort effects in some MetS components, suggesting associations between the changing environment and health outcomes in later life. This ecological association is worthy of further investigation.
PMCID: PMC3117818  PMID: 21619595
Metabolic syndrome; obesity; age-period-cohort analysis; partial least squares; Taiwan
10.  A New Approach to Age-Period-Cohort Analysis Using Partial Least Squares Regression: The Trend in Blood Pressure in the Glasgow Alumni Cohort 
PLoS ONE  2011;6(4):e19401.
Due to a problem of identification, how to estimate the distinct effects of age, time period and cohort has been a controversial issue in the analysis of trends in health outcomes in epidemiology. In this study, we propose a novel approach, partial least squares (PLS) analysis, to separate the effects of age, period, and cohort. Our example for illustration is taken from the Glasgow Alumni cohort. A total of 15,322 students (11,755 men and 3,567 women) received medical screening at the Glasgow University between 1948 and 1968. The aim is to investigate the secular trends in blood pressure over 1925 and 1950 while taking into account the year of examination and age at examination. We excluded students born before 1925 or aged over 25 years at examination and those with missing values in confounders from the analyses, resulting in 12,546 and 12,516 students for analysis of systolic and diastolic blood pressure, respectively. PLS analysis shows that both systolic and diastolic blood pressure increased with students' age, and students born later had on average lower blood pressure (SBP: −0.17 mmHg/per year [95% confidence intervals: −0.19 to −0.15] for men and −0.25 [−0.28 to −0.22] for women; DBP: −0.14 [−0.15 to −0.13] for men; −0.09 [−0.11 to −0.07] for women). PLS also shows a decreasing trend in blood pressure over the examination period. As identification is not a problem for PLS, it provides a flexible modelling strategy for age-period-cohort analysis. More emphasis is then required to clarify the substantive and conceptual issues surrounding the definitions and interpretations of age, period and cohort effects.
PMCID: PMC3083444  PMID: 21556329
11.  Simpson's Paradox, Lord's Paradox, and Suppression Effects are the same phenomenon – the reversal paradox 
This article discusses three statistical paradoxes that pervade epidemiological research: Simpson's paradox, Lord's paradox, and suppression. These paradoxes have important implications for the interpretation of evidence from observational studies. This article uses hypothetical scenarios to illustrate how the three paradoxes are different manifestations of one phenomenon – the reversal paradox – depending on whether the outcome and explanatory variables are categorical, continuous or a combination of both; this renders the issues and remedies for any one to be similar for all three. Although the three statistical paradoxes occur in different types of variables, they share the same characteristic: the association between two variables can be reversed, diminished, or enhanced when another variable is statistically controlled for. Understanding the concepts and theory behind these paradoxes provides insights into some controversial or contradictory research findings. These paradoxes show that prior knowledge and underlying causal theory play an important role in the statistical modelling of epidemiological data, where incorrect use of statistical models might produce consistent, replicable, yet erroneous results.
PMCID: PMC2254615  PMID: 18211676
12.  The most dangerous hospital or the most dangerous equation? 
Hospital mortality rates are one of the most frequently selected indicators for measuring the performance of NHS Trusts. A recent article in a national newspaper named the hospital with the highest or lowest mortality in the 2005/6 financial year; a report by the organization Dr Foster Intelligence provided information with regard to the performance of all NHS Trusts in England.
Basic statistical theory and computer simulations were used to explore the relationship between the variations in the performance of NHS Trusts and the sizes of the Trusts. Data of hospital standardised mortality ratio (HSMR) of 152 English NHS Trusts for 2005/6 were re-analysed.
A close examination of the information reveals a pattern which is consistent with a statistical phenomenon, discovered by the French mathematician de Moivre nearly 300 years ago, described in every introductory statistics textbook: namely that variation in performance indicators is expected to be greater in small Trusts and smaller in large Trusts. From a statistical viewpoint, the number of deaths in a hospital is not in proportion to the size of the hospital, but is proportional to the square root of its size. Therefore, it is not surprising to note that small hospitals are more likely to occur at the top and the bottom of league tables, whilst mortality rates are independent of hospital sizes.
This statistical phenomenon needs to be taken into account in the comparison of hospital Trusts performance, especially with regard to policy decisions.
PMCID: PMC2194686  PMID: 18005428
13.  Do the UK government's new Quality and Outcomes Framework (QOF) scores adequately measure primary care performance? A cross-sectional survey of routine healthcare data 
General practitioners' remuneration is now linked directly to the scores attained in the Quality and Outcomes Framework (QOF). The success of this approach depends in part on designing a robust and clinically meaningful set of indicators. The aim of this study was to assess the extent to which measures of health observed in practice populations are correlated with their QOF scores, after accounting for the established associations between health outcomes and socio-demographics.
QOF data for the period April 2004 to March 2005 were obtained for all general practices in two English Primary Care Trusts. These data were linked to data for emergency hospital admissions (for asthma, cancer, chronic obstructive pulmonary disease, coronary hear disease, diabetes, stroke and all other conditions) and all cause mortality for the period September 2004 to August 2005. Multilevel logistic regression models explored the association between health outcomes (hospital admission and death) and practice QOF scores (clinical, additional services and organisational domains), age, sex and socio-economic deprivation.
Higher clinical domain scores were generally associated with lower admission rates and this was significant for cancer and other conditions in PCT 2. Higher scores in the additional services domain were associated with higher admission rates, significantly so for asthma, CHD, stroke and other conditions in PCT 1 and cancer in PCT 2. Little association was observed between the organisational domain scores and admissions. The relationship between the QOF variables and mortality was less clear. Being female was associated with fewer admissions for cancer and CHD and lower mortality rates. Increasing age was mainly associated with an increased number of events. Increasing deprivation was associated with higher admission rates for all conditions and with higher mortality rates.
The associations between QOF scores and emergency admissions and mortality were small and inconsistent, whilst the impact of socio-economic deprivation on the outcomes was much stronger. These results have implications for the use of target-based remuneration of general practitioners and emphasise the need to tackle inequalities and improve the health of disadvantaged groups and the population as a whole.
PMCID: PMC2117011  PMID: 17941984
15.  Blood glucose concentration and risk of pancreatic cancer: systematic review and dose-response meta-analysis 
Objective To evaluate potential linear and non-linear dose-response relations between blood glucose and risk of pancreatic cancer.
Design Systematic review and dose-response meta-analysis of prospective observational studies.
Data sources Search of PubMed, Scopus, and related reviews before 30 November 2013 without language restriction.
Eligibility criteria Prospective studies evaluating the association between blood glucose concentration and pancreatic cancer. Retrospective and cross sectional studies excluded to avoid reverse causality.
Data extraction and synthesis Two reviewers independently extracted relevant information and assessed study quality with the Newcastle-Ottawa scale. Random effects dose-response meta-analysis was conducted to assess potential linear and non-linear dose-response relations.
Results Nine studies were included for analysis, with a total of 2408 patients with pancreatic cancer. There was a strong linear dose-response association between fasting blood glucose concentration and the rate of pancreatic cancer across the range of prediabetes and diabetes. No non-linear association was detected. The pooled rate ratio of pancreatic cancer per 0.56 mmol/L (10 mg/dL) increase in fasting blood glucose was 1.14 (95% confidence interval 1.06 to 1.22; P<0.001) without significant heterogeneity. Sensitivity analysis excluding blood glucose categories in the range of diabetes showed similar results (pooled rate ratio per 0.56 mmol/L increase in fasting blood glucose was 1.15, 95% confidence interval 1.05 to 1.27; P=0.003), strengthening the association between prediabetes and pancreatic cancer.
Conclusions Every 0.56 mmol/L increase in fasting blood glucose is associated with a 14% increase in the rate of pancreatic cancer. As prediabetes can be improved or even reversed through lifestyle changes, early detection of prediabetes coupled with lifestyle changes could represent a viable strategy to curb the increasing incidence of pancreatic cancer.
PMCID: PMC4282179  PMID: 25556126

Results 1-15 (15)