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1.  Body Mass Index, Waist-circumference and Cardiovascular Disease Risk Factors in Iranian Adults: Isfahan Healthy Heart Program 
Considering the main effect of obesity on chronic non-communicable diseases, this study was performed to assess the association between body mass index (BMI), waist-circumference (WC), cardiometabolic risk factors and to corroborate whether either or both BMI and WC are independently associated with the risk factors in a sample of Iranian adults. This cross-sectional study was performed on data from baseline survey of Isfahan Healthy Heart Program (IHHP). The study was done on 12,514 randomly-selected adults in Isfahan, Najafabad and Arak counties in 2000-2001. Ages of the subjects were recorded. Fasting blood glucose (FBG), 2-hour post-load glucose (2hpp), serum lipids, systolic and diastolic blood pressure (SBP and DBP), BMI, WC, smoking status, and total daily physical activity were determined. Increase in BMI and WC had a significant positive relation with the mean of FBG, 2hpp, SBP, DBP, serum lipids, except for HDL-C (p<0.001 for all). After adjustment for age, smoking, physical activity, socioeconomic status (SES), and BMI, the highest odds ratio (OR) (95% CI) for diabetes mellitus (DM) according to WC was 3.13 (1.93-5.08) and 1.99 (1.15-3.44) in women and men respectively. Moreover, the highest ORs based on BMI with adjustment for age, smoking, physical activity, SES, and WC were for dyslipidaemia (DLP) [1.97 (1.58-2.45) in women and 2.96 (2.41-3.63) in men]. The use of BMI or WC alone in the models caused to enhance all ORs. When both BMI and WC were entered in the model, the ORs for all risk factors, in men, according to BMI, were more compared to WC. However, in women, ORs for DM and hypertension (HTN) in WC quartiles were more than in BMI quartiles. BMI is the better predictor of DM, HTN, and DLP in men compared to WC. Conversely, in women, WC is a superior predictor than BMI, particularly for DM and HTN. Furthermore, the measurement of both WC and BMI in Iranian adults may be a better predictor of traditional risk factors of CVDs compared to BMI or WC alone.
PMCID: PMC3805889  PMID: 24288953
Body mass index; Diabetes mellitus; Dyslipidaemia; Hypertension; Obesity; Risk Factor; Waist-circumference; Iran
2.  The Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis 
Fall, Tove | Hägg, Sara | Mägi, Reedik | Ploner, Alexander | Fischer, Krista | Horikoshi, Momoko | Sarin, Antti-Pekka | Thorleifsson, Gudmar | Ladenvall, Claes | Kals, Mart | Kuningas, Maris | Draisma, Harmen H. M. | Ried, Janina S. | van Zuydam, Natalie R. | Huikari, Ville | Mangino, Massimo | Sonestedt, Emily | Benyamin, Beben | Nelson, Christopher P. | Rivera, Natalia V. | Kristiansson, Kati | Shen, Huei-yi | Havulinna, Aki S. | Dehghan, Abbas | Donnelly, Louise A. | Kaakinen, Marika | Nuotio, Marja-Liisa | Robertson, Neil | de Bruijn, Renée F. A. G. | Ikram, M. Arfan | Amin, Najaf | Balmforth, Anthony J. | Braund, Peter S. | Doney, Alexander S. F. | Döring, Angela | Elliott, Paul | Esko, Tõnu | Franco, Oscar H. | Gretarsdottir, Solveig | Hartikainen, Anna-Liisa | Heikkilä, Kauko | Herzig, Karl-Heinz | Holm, Hilma | Hottenga, Jouke Jan | Hyppönen, Elina | Illig, Thomas | Isaacs, Aaron | Isomaa, Bo | Karssen, Lennart C. | Kettunen, Johannes | Koenig, Wolfgang | Kuulasmaa, Kari | Laatikainen, Tiina | Laitinen, Jaana | Lindgren, Cecilia | Lyssenko, Valeriya | Läärä, Esa | Rayner, Nigel W. | Männistö, Satu | Pouta, Anneli | Rathmann, Wolfgang | Rivadeneira, Fernando | Ruokonen, Aimo | Savolainen, Markku J. | Sijbrands, Eric J. G. | Small, Kerrin S. | Smit, Jan H. | Steinthorsdottir, Valgerdur | Syvänen, Ann-Christine | Taanila, Anja | Tobin, Martin D. | Uitterlinden, Andre G. | Willems, Sara M. | Willemsen, Gonneke | Witteman, Jacqueline | Perola, Markus | Evans, Alun | Ferrières, Jean | Virtamo, Jarmo | Kee, Frank | Tregouet, David-Alexandre | Arveiler, Dominique | Amouyel, Philippe | Ferrario, Marco M. | Brambilla, Paolo | Hall, Alistair S. | Heath, Andrew C. | Madden, Pamela A. F. | Martin, Nicholas G. | Montgomery, Grant W. | Whitfield, John B. | Jula, Antti | Knekt, Paul | Oostra, Ben | van Duijn, Cornelia M. | Penninx, Brenda W. J. H. | Davey Smith, George | Kaprio, Jaakko | Samani, Nilesh J. | Gieger, Christian | Peters, Annette | Wichmann, H.-Erich | Boomsma, Dorret I. | de Geus, Eco J. C. | Tuomi, TiinaMaija | Power, Chris | Hammond, Christopher J. | Spector, Tim D. | Lind, Lars | Orho-Melander, Marju | Palmer, Colin Neil Alexander | Morris, Andrew D. | Groop, Leif | Järvelin, Marjo-Riitta | Salomaa, Veikko | Vartiainen, Erkki | Hofman, Albert | Ripatti, Samuli | Metspalu, Andres | Thorsteinsdottir, Unnur | Stefansson, Kari | Pedersen, Nancy L. | McCarthy, Mark I. | Ingelsson, Erik | Prokopenko, Inga
PLoS Medicine  2013;10(6):e1001474.
In this study, Prokopenko and colleagues provide novel evidence for causal relationship between adiposity and heart failure and increased liver enzymes using a Mendelian randomization study design.
Please see later in the article for the Editors' Summary
Background
The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach.
Methods and Findings
We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses.
Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI–trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03–1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1–1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p = 0.001).
Conclusions
We provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes.
Please see later in the article for the Editors' Summary
Editors' Summary
Cardiovascular disease (CVD)—disease that affects the heart and/or the blood vessels—is a major cause of illness and death worldwide. In the US, for example, coronary heart disease—a CVD in which narrowing of the heart's blood vessels by fatty deposits slows the blood supply to the heart and may eventually cause a heart attack—is the leading cause of death, and stroke—a CVD in which the brain's blood supply is interrupted—is the fourth leading cause of death. Globally, both the incidence of CVD (the number of new cases in a population every year) and its prevalence (the proportion of the population with CVD) are increasing, particularly in low- and middle-income countries. This increasing burden of CVD is occurring in parallel with a global increase in the incidence and prevalence of obesity—having an unhealthy amount of body fat (adiposity)—and of metabolic diseases—conditions such as diabetes in which metabolism (the processes that the body uses to make energy from food) is disrupted, with resulting high blood sugar and damage to the blood vessels.
Why Was This Study Done?
Epidemiological studies—investigations that record the patterns and causes of disease in populations—have reported an association between adiposity (indicated by an increased body mass index [BMI], which is calculated by dividing body weight in kilograms by height in meters squared) and cardiometabolic traits such as coronary heart disease, stroke, heart failure (a condition in which the heart is incapable of pumping sufficient amounts of blood around the body), diabetes, high blood pressure (hypertension), and high blood cholesterol (dyslipidemia). However, observational studies cannot prove that adiposity causes any particular cardiometabolic trait because overweight individuals may share other characteristics (confounding factors) that are the real causes of both obesity and the cardiometabolic disease. Moreover, it is possible that having CVD or a metabolic disease causes obesity (reverse causation). For example, individuals with heart failure cannot do much exercise, so heart failure may cause obesity rather than vice versa. Here, the researchers use “Mendelian randomization” to examine whether adiposity is causally related to various cardiometabolic traits. Because gene variants are inherited randomly, they are not prone to confounding and are free from reverse causation. It is known that a genetic variant (rs9939609) within the genome region that encodes the fat-mass- and obesity-associated gene (FTO) is associated with increased BMI. Thus, an investigation of the associations between rs9939609 and cardiometabolic traits can indicate whether obesity is causally related to these traits.
What Did the Researchers Do and Find?
The researchers analyzed the association between rs9939609 (the “instrumental variable,” or IV) and BMI, between rs9939609 and 24 cardiometabolic traits, and between BMI and the same traits using genetic and health data collected in 36 population-based studies of nearly 200,000 individuals of European descent. They then quantified the strength of the causal association between BMI and the cardiometabolic traits by calculating “IV estimators.” Higher BMI showed a causal relationship with heart failure, metabolic syndrome (a combination of medical disorders that increases the risk of developing CVD), type 2 diabetes, dyslipidemia, hypertension, increased blood levels of liver enzymes (an indicator of liver damage; some metabolic disorders involve liver damage), and several other cardiometabolic traits. All the IV estimators were similar to the BMI–cardiovascular trait associations (observational estimates) derived from the same individuals, with the exception of diabetes, where the causal estimate was higher than the observational estimate, probably because the observational estimate is based on a single BMI measurement, whereas the causal estimate considers lifetime changes in BMI.
What Do These Findings Mean?
Like all Mendelian randomization studies, the reliability of the causal associations reported here depends on several assumptions made by the researchers. Nevertheless, these findings provide support for many previously suspected and biologically plausible causal relationships, such as that between adiposity and hypertension. They also provide new insights into the causal effect of obesity on liver enzyme levels and on heart failure. In the latter case, these findings suggest that a one-unit increase in BMI might increase the incidence of heart failure by 17%. In the US, this corresponds to 113,000 additional cases of heart failure for every unit increase in BMI at the population level. Although additional studies are needed to confirm and extend these findings, these results suggest that global efforts to reduce the burden of obesity will likely also reduce the occurrence of CVD and metabolic disorders.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001474.
The American Heart Association provides information on all aspects of cardiovascular disease and tips on keeping the heart healthy, including weight management (in several languages); its website includes personal stories about stroke and heart attacks
The US Centers for Disease Control and Prevention has information on heart disease, stroke, and all aspects of overweight and obesity (in English and Spanish)
The UK National Health Service Choices website provides information about cardiovascular disease and obesity, including a personal story about losing weight
The World Health Organization provides information on obesity (in several languages)
The International Obesity Taskforce provides information about the global obesity epidemic
Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
MedlinePlus provides links to other sources of information on heart disease, on vascular disease, on obesity, and on metabolic disorders (in English and Spanish)
The International Association for the Study of Obesity provides maps and information about obesity worldwide
The International Diabetes Federation has a web page that describes types, complications, and risk factors of diabetes
doi:10.1371/journal.pmed.1001474
PMCID: PMC3692470  PMID: 23824655
3.  Are Current UK National Institute for Health and Clinical Excellence (NICE) Obesity Risk Guidelines Useful? Cross-Sectional Associations with Cardiovascular Disease Risk Factors in a Large, Representative English Population 
PLoS ONE  2013;8(7):e67764.
The National Institute for Health and Clinical Excellence (NICE) has recently released obesity guidelines for health risk. For the first time in the UK, we estimate the utility of these guidelines by relating them to the established cardiovascular disease (CVD) risk factors. Health Survey for England (HSE) 2006, a population-based cross-sectional study in England was used with a sample size of 7225 men and women aged ≥35 years (age range: 35–97 years). The following CVD risk factor outcomes were used: hypertension, diabetes, total and high density lipoprotein cholesterol, glycated haemoglobin, fibrinogen, C-reactive protein and Framingham risk score. Four NICE categories of obesity were created based on body mass index (BMI) and waist circumference (WC): no risk (up to normal BMI and low/high WC); increased risk (normal BMI & very high WC, or obese & low WC); high risk (overweight & very high WC, or obese & high WC); and very high risk (obese I & very high WC or obese II/III with any levels of WC. Men and women in the very high risk category had the highest odds ratios (OR) of having unfavourable CVD risk factors compared to those in the no risk category. For example, the OR of having hypertension for those in the very high risk category of the NICE obesity groupings was 2.57 (95% confidence interval 2.06 to 3.21) in men, and 2.15 (1.75 to 2.64) in women. Moreover, a dose-response association between the adiposity groups and most of the CVD risk factors was observed except total cholesterol in men and low HDL in women. Similar results were apparent when the Framingham risk score was the outcome of interest. In conclusion, the current NICE definitions of obesity show utility for a range of CVD risk factors and CVD risk in both men and women.
doi:10.1371/journal.pone.0067764
PMCID: PMC3699476  PMID: 23844088
4.  Are Markers of Inflammation More Strongly Associated with Risk for Fatal Than for Nonfatal Vascular Events? 
PLoS Medicine  2009;6(6):e1000099.
In a secondary analysis of a randomized trial comparing pravastatin versus placebo for the prevention of coronary and cerebral events in an elderly at-risk population, Naveed Sattar and colleagues find that inflammatory markers may be more strongly associated with risk of fatal vascular events than nonfatal vascular events.
Background
Circulating inflammatory markers may more strongly relate to risk of fatal versus nonfatal cardiovascular disease (CVD) events, but robust prospective evidence is lacking. We tested whether interleukin (IL)-6, C-reactive protein (CRP), and fibrinogen more strongly associate with fatal compared to nonfatal myocardial infarction (MI) and stroke.
Methods and Findings
In the Prospective Study of Pravastatin in the Elderly at Risk (PROSPER), baseline inflammatory markers in up to 5,680 men and women aged 70–82 y were related to risk for endpoints; nonfatal CVD (i.e., nonfatal MI and nonfatal stroke [n = 672]), fatal CVD (n = 190), death from other CV causes (n = 38), and non-CVD mortality (n = 300), over 3.2-y follow-up. Elevations in baseline IL-6 levels were significantly (p = 0.0009; competing risks model analysis) more strongly associated with fatal CVD (hazard ratio [HR] for 1 log unit increase in IL-6 1.75, 95% confidence interval [CI] 1.44–2.12) than with risk of nonfatal CVD (1.17, 95% CI 1.04–1.31), in analyses adjusted for treatment allocation. The findings were consistent in a fully adjusted model. These broad trends were similar for CRP and, to a lesser extent, for fibrinogen. The results were also similar in placebo and statin recipients (i.e., no interaction). The C-statistic for fatal CVD using traditional risk factors was significantly (+0.017; p<0.0001) improved by inclusion of IL-6 but not so for nonfatal CVD events (p = 0.20).
Conclusions
In PROSPER, inflammatory markers, in particular IL-6 and CRP, are more strongly associated with risk of fatal vascular events than nonfatal vascular events. These novel observations may have important implications for better understanding aetiology of CVD mortality, and have potential clinical relevance.
Please see later in the article for Editors' Summary
Editors' Summary
Background
Cardiovascular disease (CVD)—disease that affects the heart and/or the blood vessels—is a common cause of death in developed countries. In the USA, for example, the leading cause of death is coronary heart disease (CHD), a CVD in which narrowing of the heart's blood vessels by “atherosclerotic plaques” (fatty deposits that build up with age) slows the blood supply to the heart and may eventually cause a heart attack (myocardial infarction). Other types of CVD include stroke (in which atherosclerotic plaques interrupt the brain's blood supply) and heart failure (a condition in which the heart cannot pump enough blood to the rest of the body). Smoking, high blood pressure, high blood levels of cholesterol (a type of fat), having diabetes, and being overweight all increase a person's risk of developing CVD. Tools such as the “Framingham risk calculator” take these and other risk factors into account to assess an individual's overall risk of CVD, which can be reduced by taking drugs to reduce blood pressure or cholesterol levels (for example, pravastatin) and by making lifestyle changes.
Why Was This Study Done?
Inflammation (an immune response to injury) in the walls of blood vessels is thought to play a role in the development of atherosclerotic plaques. Consistent with this idea, several epidemiological studies (investigations of the causes and distribution of disease in populations) have shown that people with high circulating levels of markers of inflammation such as interleukin-6 (IL-6), C-reactive protein (CRP), and fibrinogen are more likely to have a stroke or a heart attack (a CVD event) than people with low levels of these markers. Although these studies have generally lumped together fatal and nonfatal CVD events, some evidence suggests that circulating inflammatory markers may be more strongly associated with fatal than with nonfatal CVD events. If this is the case, the mechanisms that lead to fatal and nonfatal CVD events may be subtly different and knowing about these differences could improve both the prevention and treatment of CVD. In this study, the researchers investigate this possibility using data collected in the Prospective Study of Pravastatin in the Elderly at Risk (PROSPER; a trial that examined pravastatin's effect on CVD development among 70–82 year olds with pre-existing CVD or an increased risk of CVD because of smoking, high blood pressure, or diabetes).
What Did the Researchers Do and Find?
The researchers used several statistical models to examine the association between baseline levels of IL-6, CRP, and fibrinogen in the trial participants and nonfatal CVD events (nonfatal heart attacks and nonfatal strokes), fatal CVD events, death from other types of CVD, and deaths from other causes during 3.2 years of follow-up. Increased levels of all three inflammatory markers were more strongly associated with fatal CVD than with nonfatal CVD after adjustment for treatment allocation and for other established CVD risk factors but this pattern was strongest for IL-6. Thus, a unit increase in the log of IL-6 levels increased the risk of fatal CVD by half but increased the risk of nonfatal CVD by significantly less. The researchers also investigated whether including these inflammatory markers in tools designed to predict an individual's CVD risk could improve the tool's ability to distinguish between individuals with a high and low risk. The addition of IL-6 to established risk factors, they report, increased this discriminatory ability for fatal CVD but not for nonfatal CVD.
What Do These Findings Mean?
These findings indicate that, at least for the elderly at-risk patients who were included in PROSPER, inflammatory markers are more strongly associated with the risk of a fatal heart attack or stroke than with nonfatal CVD events. These findings need to be confirmed in younger populations and larger studies also need to be done to discover whether the same association holds when fatal heart attacks and fatal strokes are considered separately. Nevertheless, the present findings suggest that inflammation may specifically help to promote the development of serious, potentially fatal CVD and should stimulate improved research into the use of inflammation markers to predict risk of deaths from CVD.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000099.
The MedlinePlus Encyclopedia has pages on coronary heart disease, stroke, and atherosclerosis (in English and Spanish)
MedlinePlus provides links to many other sources of information on heart diseases, vascular diseases, and stroke (in English and Spanish)
Information for patients and caregivers is provided by the American Heart Association on all aspects of cardiovascular disease, including information on inflammation and heart disease
Information is available from the British Heart Foundation on heart disease and keeping the heart healthy
More information about PROSPER is available on the Web site of the Vascular Biochemistry Department of the University of Glasgow
doi:10.1371/journal.pmed.1000099
PMCID: PMC2694359  PMID: 19554082
5.  The impact of obesity on hypertension and diabetes control following healthy Lifestyle Intervention Program in a developing country setting 
BACKGROUND:
The aim of this study was to evaluate the impact of obesity and overweight on diabetes mellitus (DM) and hypertension (HTN) control in a healthy lifestyle intervention program in Iran.
METHODS:
Within the framework of the Isfahan Healthy Heart Program (IHHP), a community trial that was conducted to prevent and control cardiovascular disease and its risk factors, two intervention counties (Isfahan and Najafabad) and one reference county (Arak) were selected. Demographic information, medical history, anti-diabetic and anti-hypertensive medications use were asked by trained interviewers in addition to physical examination and laboratory tests for 12514 adults aged more than 19 years in 2001 and were repeated for 9572 adults in 2007.
RESULTS:
In women, the frequency of HTN control change significantly neither in normal weight nor in those with high body mass index (BMI), waist circumference (WC) or waist to hip ratio (WHR). In men, the frequency of HTN control was only significant among those with high WHR, whereas the interaction between changes in intervention compared to reference area from 2001 to 2007 was significant in men with normal or high WC or WHR. In intervention area, the number of women with high BMI who controlled their DM increased significantly from 2001 to 2007 (p = 0.008), however, this figure decreased in men. In reference area, obesity indices had no significant association with DM control. The percentage of diabetic subjects with high WC who controlled their DM decreased non-significantly in intervention area compared to reference area in 2007. A non-significant increase in controlled DM among men and women with high WHR was observed between intervention and reference areas.
CONCLUSIONS:
Our lifestyle interventions did not show any improving effect on HTN or DM control among obese subjects based on different obesity indices. Other lifestyle intervention strategies are suggested.
PMCID: PMC3252770  PMID: 22247721
Hypertension; Diabetes; Obesity; Control; Prevention; Iran
6.  BMI and Risk of Serious Upper Body Injury Following Motor Vehicle Crashes: Concordance of Real-World and Computer-Simulated Observations 
PLoS Medicine  2010;7(3):e1000250.
Shankuan Zhu and colleagues use computer crash simulations, as well as real-world data, to evaluate whether driver obesity is associated with greater risk of body injury in motor vehicle crashes.
Background
Men tend to have more upper body mass and fat than women, a physical characteristic that may predispose them to severe motor vehicle crash (MVC) injuries, particularly in certain body regions. This study examined MVC-related regional body injury and its association with the presence of driver obesity using both real-world data and computer crash simulation.
Methods and Findings
Real-world data were from the 2001 to 2005 National Automotive Sampling System Crashworthiness Data System. A total of 10,941 drivers who were aged 18 years or older involved in frontal collision crashes were eligible for the study. Sex-specific logistic regression models were developed to analyze the associations between MVC injury and the presence of driver obesity. In order to confirm the findings from real-world data, computer models of obese subjects were constructed and crash simulations were performed. According to real-world data, obese men had a substantially higher risk of injury, especially serious injury, to the upper body regions including head, face, thorax, and spine than normal weight men (all p<0.05). A U-shaped relation was found between body mass index (BMI) and serious injury in the abdominal region for both men and women (p<0.05 for both BMI and BMI2). In the high-BMI range, men were more likely to be seriously injured than were women for all body regions except the extremities and abdominal region (all p<0.05 for interaction between BMI and sex). The findings from the computer simulation were generally consistent with the real-world results in the present study.
Conclusions
Obese men endured a much higher risk of injury to upper body regions during MVCs. This higher risk may be attributed to differences in body shape, fat distribution, and center of gravity between obese and normal-weight subjects, and between men and women.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Worldwide, accidents involving motor vehicles kill 1.2 million people and injure as many as 50 million people every year. Collisions between motor vehicles, between vehicles and stationary objects, or between vehicles and pedestrians are responsible for one in 50 deaths and are the 11th leading cause of death globally. Many factors contribute to the risk of motor traffic accidents and the likelihood of subsequent injury or death. These risk factors include vehicle design, vehicle speeds, road design, driver impairment through, for example, alcohol use, and other driver characteristics such as age. Faced with an ever-increasing death toll on their roads, many countries have introduced lower speed limits, mandatory seat belt use, and greater penalties for drunk driving to reduce the carnage. Road design and traffic management initiatives have also been introduced to try to reduce the incidence of road traffic accidents and cars now include many features that provide protection in crashes for their occupants such as airbags and crumple zones.
Why Was This Study Done?
Although these measures have reduced the number of crashes and casualties, a better understanding of the risk factors associated with motor vehicle crashes is needed to deal with this important public-health problem. Another major public-health problem is obesity—having excess body fat. Obesity increases the risk of heart disease and diabetes but also contributes to the severity of motor vehicle crash injuries. Men with a high body mass index (an individual's weight in kilograms divided by height in meters squared; a BMI of 30 or more indicates obesity) have a higher risk of death after a motor vehicle accident than men with a normal BMI (18.5–24.9). This association between death and obesity is not seen in women, however, possibly because men and women accumulate fat on different parts of their body and the resultant difference in body shape could affect how male and female bodies move during traffic collisions and how much protection existing car safety features afford them. In this study, therefore, the researchers investigated how driver obesity affects the risk of serious injuries in different parts of the body following real and simulated motor vehicle crashes in men and women.
What Did the Researchers Do and Find?
The researchers extracted data about injuries and BMIs for nearly 11,000 adult men and women who were involved in a frontal motor vehicle collision between 2001 and 2005 from the Crashworthiness Data System of the US National Automotive Sampling System. They then used detailed statistical methods to look for associations between specific injuries and driver obesity. The researchers also constructed computer models of obese drivers and subjected these models to simulated crashes. Their analysis of the real-world data showed that obese men had a substantially higher risk of injury to the upper body (the head, face, chest, and spine) than men with a normal weight. Serious injury in the abdominal region was most likely at low and high BMIs for both men and women. Finally, obese men were more likely to be seriously injured than obese women for all body regions except the extremities and the abdominal region. The researchers' computer simulations confirmed many of these real-world findings.
What Do These Findings Mean?
These findings suggest that obese men have a higher risk of injury, particularly to their upper body, from motor vehicle crashes than men with a normal body weight or than obese women. The researchers suggest that this higher risk may be attributed to differences in body shape, fat distribution, and center of gravity between obese and normal weight individuals and between men and women. These findings, although limited by missing data, suggest that motor vehicle safety features should be adjusted to take into account the ongoing obesity epidemic. Currently, two-thirds of people in the US are overweight or obese, yet a crash test dummy with a normal BMI is still used during the design of car cabins. Finally, although more studies are needed to understand the biomechanical responses of the human body during vehicle collisions, the findings in this study could aid the identification of groups of people at particularly high risk of injury or death on the roads who could then be helped to reduce their risk.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000250.
Wikipedia has a page on traffic collision (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
The World Health Organization has information about road traffic injuries as a public-health problem; its World report on road traffic injury prevention is available in several languages
The US Centers for Disease Control and Prevention provides detailed information about overweight and obesity (in several languages)
MedlinePlus provides links to further resources about obesity (in English and Spanish)
The US National Automotive Sampling System Crashworthiness Data System contains detailed data on thousands of US motor vehicle crashes
doi:10.1371/journal.pmed.1000250
PMCID: PMC2846859  PMID: 20361024
7.  Metabolic Signatures of Adiposity in Young Adults: Mendelian Randomization Analysis and Effects of Weight Change 
PLoS Medicine  2014;11(12):e1001765.
In this study, Wurtz and colleagues investigated to what extent elevated body mass index (BMI) within the normal weight range has causal influences on the detailed systemic metabolite profile in early adulthood using Mendelian randomization analysis.
Please see later in the article for the Editors' Summary
Background
Increased adiposity is linked with higher risk for cardiometabolic diseases. We aimed to determine to what extent elevated body mass index (BMI) within the normal weight range has causal effects on the detailed systemic metabolite profile in early adulthood.
Methods and Findings
We used Mendelian randomization to estimate causal effects of BMI on 82 metabolic measures in 12,664 adolescents and young adults from four population-based cohorts in Finland (mean age 26 y, range 16–39 y; 51% women; mean ± standard deviation BMI 24±4 kg/m2). Circulating metabolites were quantified by high-throughput nuclear magnetic resonance metabolomics and biochemical assays. In cross-sectional analyses, elevated BMI was adversely associated with cardiometabolic risk markers throughout the systemic metabolite profile, including lipoprotein subclasses, fatty acid composition, amino acids, inflammatory markers, and various hormones (p<0.0005 for 68 measures). Metabolite associations with BMI were generally stronger for men than for women (median 136%, interquartile range 125%–183%). A gene score for predisposition to elevated BMI, composed of 32 established genetic correlates, was used as the instrument to assess causality. Causal effects of elevated BMI closely matched observational estimates (correspondence 87%±3%; R2 = 0.89), suggesting causative influences of adiposity on the levels of numerous metabolites (p<0.0005 for 24 measures), including lipoprotein lipid subclasses and particle size, branched-chain and aromatic amino acids, and inflammation-related glycoprotein acetyls. Causal analyses of certain metabolites and potential sex differences warrant stronger statistical power. Metabolite changes associated with change in BMI during 6 y of follow-up were examined for 1,488 individuals. Change in BMI was accompanied by widespread metabolite changes, which had an association pattern similar to that of the cross-sectional observations, yet with greater metabolic effects (correspondence 160%±2%; R2 = 0.92).
Conclusions
Mendelian randomization indicates causal adverse effects of increased adiposity with multiple cardiometabolic risk markers across the metabolite profile in adolescents and young adults within the non-obese weight range. Consistent with the causal influences of adiposity, weight changes were paralleled by extensive metabolic changes, suggesting a broadly modifiable systemic metabolite profile in early adulthood.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Adiposity—having excessive body fat—is a growing global threat to public health. Body mass index (BMI, calculated by dividing a person's weight in kilograms by their height in meters squared) is a coarse indicator of excess body weight, but the measure is useful in large population studies. Compared to people with a lean body weight (a BMI of 18.5–24.9 kg/m2), individuals with higher BMI have an elevated risk of developing life-shortening cardiometabolic diseases—cardiovascular diseases that affect the heart and/or the blood vessels (for example, heart failure and stroke) and metabolic diseases that affect the cellular chemical reactions that sustain life (for example, diabetes). People become unhealthily fat by consuming food and drink that contains more energy (calories) than they need for their daily activities. So adiposity can be prevented and reversed by eating less and exercising more.
Why Was This Study Done?
Epidemiological studies, which record the patterns of risk factors and disease in populations, suggest that the illness and death associated with excess body weight is partly attributable to abnormalities in how individuals with high adiposity metabolize carbohydrates and fats, leading to higher blood sugar and cholesterol levels. Further, adiposity is also associated with many other deviations in the metabolic profile than these commonly measured risk factors. However, epidemiological studies cannot prove that adiposity causes specific changes in a person's systemic (overall) metabolic profile because individuals with high BMI may share other characteristics (confounding factors) that are the actual causes of both adiposity and metabolic abnormalities. Moreover, having a change in some aspect of metabolism could also lead to adiposity, rather than vice versa (reverse causation). Importantly, if there is a causal effect of adiposity on cardiometabolic risk factor levels, it might be possible to prevent the progression towards cardiometabolic diseases by weight loss. Here, the researchers use “Mendelian randomization” to examine whether increased BMI within the normal and overweight range is causally influencing the metabolic risk factors from many biological pathways during early adulthood. Because gene variants are inherited randomly, they are not prone to confounding and are free from reverse causation. Several gene variants are known to lead to modestly increased BMI. Thus, an investigation of the associations between these gene variants and risk factors across the systemic metabolite profile in a population of healthy individuals can indicate whether higher BMI is causally related to known and novel metabolic risk factors and higher cardiometabolic disease risk.
What Did the Researchers Do and Find?
The researchers measured the BMI of 12,664 adolescents and young adults (average BMI 24.7 kg/m2) living in Finland and the blood levels of 82 metabolites in these young individuals at a single time point. Statistical analysis of these data indicated that elevated BMI was adversely associated with numerous cardiometabolic risk factors. For example, elevated BMI was associated with raised levels of low-density lipoprotein, “bad” cholesterol that increases cardiovascular disease risk. Next, the researchers used a gene score for predisposition to increased BMI, composed of 32 gene variants correlated with increased BMI, as an “instrumental variable” to assess whether adiposity causes metabolite abnormalities. The effects on the systemic metabolite profile of a 1-kg/m2 increment in BMI due to genetic predisposition closely matched the effects of an observed 1-kg/m2 increment in adulthood BMI on the metabolic profile. That is, higher levels of adiposity had causal effects on the levels of numerous blood-based metabolic risk factors, including higher levels of low-density lipoprotein cholesterol and triglyceride-carrying lipoproteins, protein markers of chronic inflammation and adverse liver function, impaired insulin sensitivity, and elevated concentrations of several amino acids that have recently been linked with the risk for developing diabetes. Elevated BMI also causally led to lower levels of certain high-density lipoprotein lipids in the blood, a marker for the risk of future cardiovascular disease. Finally, an examination of the metabolic changes associated with changes in BMI in 1,488 young adults after a period of six years showed that those metabolic measures that were most strongly associated with BMI at a single time point likewise displayed the highest responsiveness to weight change over time.
What Do These Findings Mean?
These findings suggest that increased adiposity has causal adverse effects on multiple cardiometabolic risk markers in non-obese young adults beyond the effects on cholesterol and blood sugar. Like all Mendelian randomization studies, the reliability of the causal association reported here depends on several assumptions made by the researchers. Nevertheless, these findings suggest that increased adiposity has causal adverse effects on multiple cardiometabolic risk markers in non-obese young adults. Importantly, the results of both the causal effect analyses and the longitudinal study suggest that there is no threshold below which a BMI increase does not adversely affect the metabolic profile, and that a systemic metabolic profile linked with high cardiometabolic disease risk that becomes established during early adulthood can be reversed. Overall, these findings therefore highlight the importance of weight reduction as a key target for metabolic risk factor control among young adults.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001765.
The Computational Medicine Research Team of the University of Oulu has a webpage that provides further information on metabolite profiling by high-throughput NMR metabolomics
The World Health Organization provides information on obesity (in several languages)
The Global Burden of Disease Study website provides the latest details about global obesity trends
The UK National Health Service Choices website provides information about obesity, cardiovascular disease, and type 2 diabetes (including some personal stories)
The American Heart Association provides information on all aspects of cardiovascular disease and diabetes and on keeping healthy; its website includes personal stories about heart attacks, stroke, and diabetes
The US Centers for Disease Control and Prevention has information on all aspects of overweight and obesity and information about heart disease, stroke, and diabetes
MedlinePlus provides links to other sources of information on heart disease, vascular disease, and obesity (in English and Spanish)
Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
doi:10.1371/journal.pmed.1001765
PMCID: PMC4260795  PMID: 25490400
8.  Gender-related differences in the prevalence of cardiovascular disease risk factors and their correlates in urban Tanzania 
Background
Urban areas in Africa suffer a serious problem with dual burden of infectious diseases and emerging chronic diseases such as cardiovascular diseases (CVD) and diabetes which pose a serious threat to population health and health care resources. However in East Africa, there is limited literature in this research area. The objective of this study was to examine the prevalence of cardiovascular disease risk factors and their correlates among adults in Temeke, Dar es Salaam, Tanzania. Results of this study will help inform future research and potential preventive and therapeutic interventions against such chronic diseases.
Methods
The study design was a cross sectional epidemiological study. A total of 209 participants aged between 44 and 66 years were included in the study. A structured questionnaire was used to evaluate socioeconomic and lifestyle characteristics. Blood samples were collected and analyzed to measure lipid profile and fasting glucose levels. Cardiovascular risk factors were defined using World Health Organization criteria.
Results
The age-adjusted prevalence of obesity (BMI ≥ 30) was 13% and 35%, among men and women (p = 0.0003), respectively. The prevalence of abdominal obesity was 11% and 58% (p < 0.0001), and high WHR (men: >0.9, women: >0.85) was 51% and 73% (p = 0.002) for men and women respectively. Women had 4.3 times greater odds of obesity (95% CI: 1.9–10.1), 14.2–fold increased odds for abdominal adiposity (95% CI: 5.8–34.6), and 2.8 times greater odds of high waist-hip-ratio (95% CI: 1.4–5.7), compared to men. Women had more than three-fold greater odds of having metabolic syndrome (p = 0.001) compared to male counterparts, including abdominal obesity, low HDL-cholesterol, and high fasting blood glucose components. In contrast, female participants had 50% lower odds of having hypertension, compared to men (95%CI: 0.3–1.0). Among men, BMI and waist circumference were significantly correlated with blood pressure, triglycerides, total, LDL-, and HDL-cholesterol (BMI only), and fasting glucose; in contrast, only blood pressure was positively associated with BMI and waist circumference in women.
Conclusion
The prevalence of CVD risk factors was high in this population, particularly among women. Health promotion, primary prevention, and health screening strategies are needed to reduce the burden of cardiovascular disease in Tanzania.
doi:10.1186/1471-2261-9-30
PMCID: PMC2723083  PMID: 19615066
9.  Sustained and Shorter Bouts of Physical Activity are Related to Cardiovascular Health 
Purpose
Whereas greater physical activity (PA) is known to prevent cardiovascular disease (CVD), the relative importance of performing PA in sustained bouts of activity versus shorter bouts of activity on CVD risk is not known. The objective of this study was to investigate the relationship between moderate-to-vigorous physical activity (MVPA), measured in bouts ≥10 minutes and <10 minutes, and CVD risk factors in a well-characterized, community-based sample of white adults.
Methods
We conducted a cross-sectional analysis of 2109 Framingham Heart Study Third Generation participants (mean age 47 years, 55% women) who underwent objective assessment of PA by accelerometry over 5–7 days. Total MVPA, MVPA done in bouts ≥10 minutes (MVPA10+), and MVPA done in bouts <10 minutes (MVPA<10) were calculated. MVPA exposures were related to individual CVD risk factors, including measures of adiposity and blood lipid and glucose levels, using linear and logistic regression.
Results
Total MVPA was significantly associated with higher high-density lipoprotein (HDL) levels, and with lower triglycerides, BMI, waist circumference and Framingham risk score (P <0.0001). MVPA<10 showed similar statistically significant associations with these CVD risk factors (P <0.001). Compliance with national guidelines (≥150 minutes of total MVPA) was significantly related to lower BMI, triglycerides, Framingham risk score, waist circumference, higher HDL, and a lower prevalence of obesity and impaired fasting glucose (P < 0.001 for all).
Conclusions
Our cross-sectional observations on a large middle-aged community-based sample confirm a positive association of MVPA with a healthier CVD risk factor profile, and indicate that accruing physical activity in bouts <10 minutes may favorably influence cardiometabolic risk. Additional investigations are warranted to confirm our findings.
doi:10.1249/MSS.0b013e31826beae5
PMCID: PMC4166425  PMID: 22895372
accelerometer; heart disease; exercise; guidelines
10.  The Effect of Rural-to-Urban Migration on Obesity and Diabetes in India: A Cross-Sectional Study 
PLoS Medicine  2010;7(4):e1000268.
Shah Ebrahim and colleagues examine the distribution of obesity, diabetes, and other cardiovascular risk factors among urban migrant factory workers in India, together with their rural siblings. The investigators identify patterns of change of cardiovascular risk factors associated with urban migration.
Background
Migration from rural areas of India contributes to urbanisation and may increase the risk of obesity and diabetes. We tested the hypotheses that rural-to-urban migrants have a higher prevalence of obesity and diabetes than rural nonmigrants, that migrants would have an intermediate prevalence of obesity and diabetes compared with life-long urban and rural dwellers, and that longer time since migration would be associated with a higher prevalence of obesity and of diabetes.
Methods and Findings
The place of origin of people working in factories in north, central, and south India was identified. Migrants of rural origin, their rural dwelling sibs, and those of urban origin together with their urban dwelling sibs were assessed by interview, examination, and fasting blood samples. Obesity, diabetes, and other cardiovascular risk factors were compared. A total of 6,510 participants (42% women) were recruited. Among urban, migrant, and rural men the age- and factory-adjusted percentages classified as obese (body mass index [BMI] >25 kg/m2) were 41.9% (95% confidence interval [CI] 39.1–44.7), 37.8% (95% CI 35.0–40.6), and 19.0% (95% CI 17.0–21.0), respectively, and as diabetic were 13.5% (95% CI 11.6–15.4), 14.3% (95% CI 12.2–16.4), and 6.2% (95% CI 5.0–7.4), respectively. Findings for women showed similar patterns. Rural men had lower blood pressure, lipids, and fasting blood glucose than urban and migrant men, whereas no differences were seen in women. Among migrant men, but not women, there was weak evidence for a lower prevalence of both diabetes and obesity among more recent (≤10 y) migrants.
Conclusions
Migration into urban areas is associated with increases in obesity, which drive other risk factor changes. Migrants have adopted modes of life that put them at similar risk to the urban population. Gender differences in some risk factors by place of origin are unexpected and require further exploration.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
India, like the rest of the world, is experiencing an epidemic of diabetes, a chronic disease characterized by dangerous levels of sugar in the blood that cause cardiovascular and kidney disease, which lower life expectancy. The prevalence of diabetes (the proportion of the population with diabetes) has been increasing steadily in India over recent decades, particularly in urban areas. In 1984, only 5% of adults living in the towns and cities of India had diabetes, but by 2004, 15% of adults in urban areas were affected by diabetes. In rural areas of India, diabetes is less common than in urban areas but even here, the prevalence of diabetes is now 6%. Obesity—too much body fat—is a major risk factor for diabetes and, in parallel with the greater increase in diabetes in urban India compared to rural India, there has been a greater increase in obesity in urban areas than in rural areas.
Why Was This Study Done?
Experts think that the increasing prevalence of obesity and diabetes in India (and in other developing countries) is caused in part by increased consumption of saturated fats and sugars and by reduced physical activity, and that these changes are related to urbanization—urban expansion into the countryside and migration from rural to urban areas. If living in an urban setting is a major determinant of obesity and diabetes risk, then people migrating into urban areas should acquire the high risk of the urban population for these two conditions. In this cross-sectional study (a study in which participants are studied at a single time point), the researchers investigate whether rural to urban migrants in India have a higher prevalence of obesity and diabetes than rural nonmigrants. They also ask whether migrants have a prevalence of obesity and diabetes intermediate between that of life-long urban and rural dwellers and whether a longer time since migration is associated with a higher prevalence of obesity and diabetes.
What Did the Researchers Do and Find?
The researchers recruited rural-urban migrants working in four Indian factories in north, central, and south regions and their spouses (if they were living in the same town) into their study. Each migrant worker and spouse asked one nonmigrant brother or sister (sibling) still living in their place of origin to join the study. The researchers also enrolled nonmigrant factory workers and their urban siblings into the study. All the participants (more than 6,500 in total) answered questions about their diet and physical activity and had their fasting blood sugar and their body mass index (BMI; weight in kg divided by height in meters squared) measured; participants with a fasting blood sugar of more than 7.0 nmol/l or a BMI of more than 25 kg/m2 were classified as diabetic or obese, respectively. 41.9% and 37.8% of the urban and migrant men, respectively, but only 19.0% of the rural men were obese. Similarly, 13.5% and 14.3% of the urban and migrant men, respectively, but only 6.2% of the rural men had diabetes. Patterns of obesity and diabetes among the women participants were similar. Finally, although the prevalence of diabetes and obesity was lower in the most recent male migrants than in those who had moved more than 10 years previously, this difference was small and not seen in women migrants.
What Do These Findings Mean?
These findings show that rural-urban migration in India is associated with rapid increases in obesity and in diabetes. They also show that the migrants have adopted modes of life (for example, reduced physical activity) that put them at a similar risk for obesity and diabetes as the urban population. The findings do not show, however, that migrants have an intermediate prevalence of obesity and diabetes compared to urban and rural dwellers and provide only weak support for the idea that a longer time since migration is associated with a higher risk of obesity and diabetes. Although the study's cross-sectional design means that the researchers could not investigate how risk factors for diabetes evolve over time, these findings suggest that urbanization is helping to drive the diabetes epidemic in India. Thus, targeting migrants and their families for health promotion activities and for treatment of risk factors for obesity and diabetes might help to slow the progress of the epidemic.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000268.
The International Diabetes Federation provides information about all aspects of diabetes, including information on diabetes in Southeast Asia (in English, French, and Spanish)
DiabetesIndia.com provides information on the Indian Task Forces on diabetes care in India
Diabetes Foundation (India) has an international collaborative research focus and provides information about health promotion for diabetes; it has also produced consensus guidelines on dietary change for prevention of diabetes in India
The US National Diabetes Information Clearinghouse provides detailed information about diabetes for patients, health care professionals, and the general public (in English and Spanish)
MedlinePlus provides links to further resources and advice about diabetes (in English and Spanish)
doi:10.1371/journal.pmed.1000268
PMCID: PMC2860494  PMID: 20436961
11.  Personalized Prediction of Lifetime Benefits with Statin Therapy for Asymptomatic Individuals: A Modeling Study 
PLoS Medicine  2012;9(12):e1001361.
In a modeling study conducted by Myriam Hunink and colleagues, a population-based cohort from Rotterdam is used to predict the possible lifetime benefits of statin therapy, on a personalized basis.
Background
Physicians need to inform asymptomatic individuals about personalized outcomes of statin therapy for primary prevention of cardiovascular disease (CVD). However, current prediction models focus on short-term outcomes and ignore the competing risk of death due to other causes. We aimed to predict the potential lifetime benefits with statin therapy, taking into account competing risks.
Methods and Findings
A microsimulation model based on 5-y follow-up data from the Rotterdam Study, a population-based cohort of individuals aged 55 y and older living in the Ommoord district of Rotterdam, the Netherlands, was used to estimate lifetime outcomes with and without statin therapy. The model was validated in-sample using 10-y follow-up data. We used baseline variables and model output to construct (1) a web-based calculator for gains in total and CVD-free life expectancy and (2) color charts for comparing these gains to the Systematic Coronary Risk Evaluation (SCORE) charts. In 2,428 participants (mean age 67.7 y, 35.5% men), statin therapy increased total life expectancy by 0.3 y (SD 0.2) and CVD-free life expectancy by 0.7 y (SD 0.4). Age, sex, smoking, blood pressure, hypertension, lipids, diabetes, glucose, body mass index, waist-to-hip ratio, and creatinine were included in the calculator. Gains in total and CVD-free life expectancy increased with blood pressure, unfavorable lipid levels, and body mass index after multivariable adjustment. Gains decreased considerably with advancing age, while SCORE 10-y CVD mortality risk increased with age. Twenty-five percent of participants with a low SCORE risk achieved equal or larger gains in CVD-free life expectancy than the median gain in participants with a high SCORE risk.
Conclusions
We developed tools to predict personalized increases in total and CVD-free life expectancy with statin therapy. The predicted gains we found are small. If the underlying model is validated in an independent cohort, the tools may be useful in discussing with patients their individual outcomes with statin therapy.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Cardiovascular disease (CVD) affects the heart and/or the blood vessels and is a major cause of illness and death worldwide. In the US, for example, coronary heart disease—a CVD in which narrowing of the heart's blood vessels by fatty deposits slows the blood supply to the heart and may eventually cause a heart attack—is the leading cause of death, and stroke—a CVD in which the brain's blood supply is interrupted—is the fourth leading cause of death. Established risk factors for CVD include smoking, high blood pressure, obesity, and high blood levels of a fat called low-density lipoprotein (“bad cholesterol”). Because many of these risk factors can be modified by lifestyle changes and by drugs, CVD can be prevented. Thus, physicians can assess a healthy individual's risk of developing CVD using a CVD prediction model (equations that take into account the CVD risk factors to which the individual is exposed) and can then recommend lifestyle changes and medications to reduce that individual's CVD risk.
Why Was This Study Done?
Current guidelines recommend that asymptomatic (healthy) individuals whose likely CVD risk is high should be encouraged to take statins—cholesterol-lowering drugs—as a preventative measure. Statins help to prevent CVD in healthy people with a high predicted risk of CVD, but, like all medicines, they have some unwanted side effects, so it is important that physicians can communicate both the benefits and drawbacks of statins to their patients in a way that allows them to make an informed decision about taking these drugs. Telling a patient that statins will reduce his or her short-term risk of CVD is not always helpful—patients really need to know the potential lifetime benefits of statin therapy. That is, they need to know how much longer they might live if they take statins. Here, the researchers use a mathematical model to predict the personalized lifetime benefits (increased total and CVD-free life expectancy) of statin therapy for individuals without a history of CVD.
What Did the Researchers Do and Find?
The researchers used the Rotterdam Ischemic Heart Disease & Stroke Computer Simulation (RISC) model, which simulates the life courses of individuals through six health states, from well through to CVD or non-CVD death, to estimate lifetime outcomes with and without statin therapy in a population of healthy elderly individuals. They then used these outcomes and information on baseline risk factors to develop a web-based calculator suitable for personalized prediction of the lifetime benefits of statins in routine clinical practice. The model estimated that statin therapy increases average life expectancy in the study population by 0.3 years and average CVD-free life expectancy by 0.7 years. The gains in total and CVD-free life expectancy associated with statin therapy increased with blood pressure, unfavorable cholesterol levels, and body mass index (an indicator of body fat) but decreased with age. Notably, the web-based calculator predicted that some individuals with a low ten-year CVD risk might achieve a similar or larger gain in CVD-free life expectancy with statin therapy than some individuals with a high ten-year risk. So, for example, both a 55-year-old non-smoking woman with a ten-year CVD mortality risk of 2% (a two in a hundred chance of dying of CVD within ten years) and a 65-year-old male smoker with a ten-year CVD mortality risk of 15% might both gain one year of CVD-free life expectancy with statin therapy.
What Do These Findings Mean?
These findings suggest that statin therapy can lead on average to small gains in total life expectancy and slightly larger gains in CVD-free life expectancy among healthy individuals, and show that life expectancy benefits can be predicted using an individual's risk factor profile. The accuracy and generalizability of these findings is limited by the assumptions included in the model (in particular, the model did not allow for the known side effects of statin therapy) and by the data fed into it—importantly, the risk prediction model needs to be validated using an independent dataset. If future research confirms the findings of this study, the researchers' web-based calculator could provide complementary information to the currently recommended ten-year CVD mortality risk assessment. Whether communication of personalized outcomes will ultimately result in better clinical outcomes remains to be seen, however, because patients may be less likely to choose statin therapy when provided with more information about its likely benefits.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001361.
The web-based calculator for personalized prediction of lifetime benefits with statin therapy is available (after agreement to software license)
The American Heart Association provides information about many types of cardiovascular disease for patients, carers, and professionals, including information about drug therapy for cholesterol and a heart attack risk calculator
The UK National Health Service Choices website provides information about cardiovascular disease and about statins
Information is available from the British Heart Foundation on heart disease and keeping the heart healthy; information is also available on statins, including personal stories about deciding to take statins
The US National Heart Lung and Blood Institute provides information on a wide range of cardiovascular diseases
The European Society of Cardiology's cardiovascular disease risk assessment model (SCORE) is available
MedlinePlus provides links to many other sources of information on heart diseases, vascular diseases, stroke, and statins (in English and Spanish)
doi:10.1371/journal.pmed.1001361
PMCID: PMC3531501  PMID: 23300388
12.  Leptin and adiponectin in relation to body fat percentage, waist to hip ratio and the apoB/apoA1 ratio in Asian Indian and Caucasian men and women 
Background
Asian Indian immigrants have an increased risk for developing cardiovascular disease (CVD); however, there is very little data examining how the adipokines leptin and adiponectin relate to CVD risk factors such as body fat percentage (BF%), waist to hip ratio (WHR) and the apoB/apoA1 ratio in Asian Indian men and women living in Canada.
Subjects and methods
A cross-sectional study comparing leptin, adiponectin, lipoproteins and anthropometric parameters in Asian Indian men and women to Caucasian men and women (4 groups). Anthropometric data (BMI, BF%, WHR), circulating lipids (apoA1, apoB, total cholesterol, and HDL-cholesterol), leptin and adiponectin were measured.
Results
Asian Indian men and women had higher leptin and lower adiponectin concentrations then Caucasian men and women, respectively. Leptin (positively) and adiponectin (negatively) correlated with anthropometric parameters and lipoproteins in all four groups. Using stepwise forward multiple regression, a model including TC/HDL-C ratio, WHR, BF%, hip circumference and waist circumference predicted 74.2% of leptin concentration in men. In women, apoB, BF%, waist circumference and age predicted 77.5% of leptin concentration. Adiponectin concentrations in men were predicted (30.2%) by HDL-C, total cholesterol, hip circumference and BF% while in women 41.2% of adiponectin concentration was predicted by the apoB/apoA1 ratio, WHR and age.
Conclusion
As is evident from our data, there is a strong relationship between leptin, adiponectin, and abdominal obesity with increased CVD risk, as assessed by the apoB/apoA1 ratio. Dysregulation of these parameters may account for the increased risk of CVD in Asian Indians.
doi:10.1186/1743-7075-3-18
PMCID: PMC1479824  PMID: 16606459
13.  Risk of Cardiovascular Disease and Total Mortality in Adults with Type 1 Diabetes: Scottish Registry Linkage Study 
PLoS Medicine  2012;9(10):e1001321.
Helen Colhoun and colleagues report findings from a Scottish registry linkage study regarding contemporary risks for cardiovascular events and all-cause mortality among individuals diagnosed with type 1 diabetes.
Background
Randomized controlled trials have shown the importance of tight glucose control in type 1 diabetes (T1DM), but few recent studies have evaluated the risk of cardiovascular disease (CVD) and all-cause mortality among adults with T1DM. We evaluated these risks in adults with T1DM compared with the non-diabetic population in a nationwide study from Scotland and examined control of CVD risk factors in those with T1DM.
Methods and Findings
The Scottish Care Information-Diabetes Collaboration database was used to identify all people registered with T1DM and aged ≥20 years in 2005–2007 and to provide risk factor data. Major CVD events and deaths were obtained from the national hospital admissions database and death register. The age-adjusted incidence rate ratio (IRR) for CVD and mortality in T1DM (n = 21,789) versus the non-diabetic population (3.96 million) was estimated using Poisson regression. The age-adjusted IRR for first CVD event associated with T1DM versus the non-diabetic population was higher in women (3.0: 95% CI 2.4–3.8, p<0.001) than men (2.3: 2.0–2.7, p<0.001) while the IRR for all-cause mortality associated with T1DM was comparable at 2.6 (2.2–3.0, p<0.001) in men and 2.7 (2.2–3.4, p<0.001) in women. Between 2005–2007, among individuals with T1DM, 34 of 123 deaths among 10,173 who were <40 years and 37 of 907 deaths among 12,739 who were ≥40 years had an underlying cause of death of coma or diabetic ketoacidosis. Among individuals 60–69 years, approximately three extra deaths per 100 per year occurred among men with T1DM (28.51/1,000 person years at risk), and two per 100 per year for women (17.99/1,000 person years at risk). 28% of those with T1DM were current smokers, 13% achieved target HbA1c of <7% and 37% had very poor (≥9%) glycaemic control. Among those aged ≥40, 37% had blood pressures above even conservative targets (≥140/90 mmHg) and 39% of those ≥40 years were not on a statin. Although many of these risk factors were comparable to those previously reported in other developed countries, CVD and mortality rates may not be generalizable to other countries. Limitations included lack of information on the specific insulin therapy used.
Conclusions
Although the relative risks for CVD and total mortality associated with T1DM in this population have declined relative to earlier studies, T1DM continues to be associated with higher CVD and death rates than the non-diabetic population. Risk factor management should be improved to further reduce risk but better treatment approaches for achieving good glycaemic control are badly needed.
Please see later in the article for the Editors' Summary
Editors' Summary
Background. People with diabetes are more likely to have cardiovascular disease such as heart attacks and strokes. They also have a higher risk of dying prematurely from any cause. Controlling blood sugar (glucose), blood pressure, and cholesterol can help reduce these risks. Some people with type 1 diabetes can achieve tight blood glucose control through a strict regimen that includes a carefully calculated diet, frequent physical activity, regular blood glucose testing several times a day, and multiple daily doses of insulin. Other drugs can reduce blood pressure and cholesterol levels. Keeping one's weight in the normal range and not smoking are important ways in which all people, including those with type 1 diabetes can reduce their risks of heart disease and premature death.
Why Was This Study Done? Researchers and doctors have known for almost two decades what patients with type 1 diabetes can do to minimize the complications from the disease and thereby reduce their risks for cardiovascular disease and early death. So for some time now, patients should have been treated and counseled accordingly. This study was done to evaluate the current risks for have cardiovascular disease and premature death amongst people living with type 1 diabetes in a high-income country (Scotland).
What Did the Researchers Do and Find? From a national register of all people with type 1 diabetes in Scotland, the researchers selected those who were older than 20 years and alive at any time from January 2005 to May 2008. This included about 19,000 people who had been diagnosed with type 1 diabetes before 2005. Another 2,600 were diagnosed between 2005 and 2008. They also obtained data on heart attacks and strokes in these patients from hospital records and on deaths from the natural death register. To obtain a good picture of the current relative risks, they compared the patients with type 1 diabetes with the non-diabetic general Scottish population with regard to the risk of heart attacks/strokes and death from all causes. They also collected information on how well the people with diabetes controlled their blood glucose, on their weight, and whether they smoked.
They found that the current risks compared with the general Scottish population are quite a bit lower than those of people with type 1 diabetes in earlier decades. However, people with type 1 diabetes in Scotland still have much higher (more than twice) the risk of heart attacks, strokes, or premature death than the general population. Moreover, the researchers found a high number of deaths in younger people with diabetes from coma—caused by either too much blood sugar (hyperglycemia) or too little (hypoglycemia). Severe hyperglycemia and hypoglycemia happen when blood glucose control is poor. When the scientists looked at test results for HbA1c levels (a test that is done once or twice a year to see how well patients controlled their blood sugar over the previous 3 months) for all patients, they found that the majority of them did not come close to controlling their blood glucose within the recommended range.
When the researchers compared body mass index (a measure of weight that takes height into account) and smoking between the people with type 1 diabetes and the general population, they found similar proportions of smokers and overweight or obese people.
What Do these Findings Mean? The results represent a snapshot of the recent situation regarding complications from type 1 diabetes in the Scottish population. The results suggest that within this population, strategies over the past two decades to reduce complications from type 1 diabetes that cause cardiovascular disease and death are working, in principle. However, there is much need for further improvement. This includes the urgent need to understand why so few people with type 1 diabetes achieve good control of their blood sugar, and what can be done to improve this situation. It is also important to put more effort into keeping people with diabetes from taking up smoking or getting them to quit, as well as preventing them from getting overweight or promoting weight reduction, because this could further reduce the risks of cardiovascular disease and premature death.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001321
National Diabetes Information Clearinghouse, a service of the US National Institute of Diabetes and Digestive and Kidney Diseases, has information on heart disease and diabetes, on general complications of diabetes, and on the HbA1c test (on this site and some others called A1C test) that measures control of blood sugar over the past 3 months
Diabetes.co.uk provides general information on type 1 diabetes, its complications, and what people with the disease can do to reduce their risks
The Canadian Diabetes Association offers a cardiovascular risk self-assessment tool and other relevant information
The American Diabetes Association has information on the benefits and challenges of tight blood sugar control and how it is tested
The Juvenile Diabetes Research Foundation funds research to prevent, cure, and treat type 1 diabetes
Diabetes UK provides extensive information on diabetes for patients, carers, and clinicians
doi:10.1371/journal.pmed.1001321
PMCID: PMC3462745  PMID: 23055834
14.  Pregnancy Weight Gain and Childhood Body Weight: A Within-Family Comparison 
PLoS Medicine  2013;10(10):e1001521.
David Ludwig and colleagues examine the within-family relationship between pregnancy weight gain and the offspring's childhood weight gain, thereby reducing the influence of genes and environment.
Please see later in the article for the Editors' Summary
Background
Excessive pregnancy weight gain is associated with obesity in the offspring, but this relationship may be confounded by genetic and other shared influences. We aimed to examine the association of pregnancy weight gain with body mass index (BMI) in the offspring, using a within-family design to minimize confounding.
Methods and Findings
In this population-based cohort study, we matched records of all live births in Arkansas with state-mandated data on childhood BMI collected in public schools (from August 18, 2003 to June 2, 2011). The cohort included 42,133 women who had more than one singleton pregnancy and their 91,045 offspring. We examined how differences in weight gain that occurred during two or more pregnancies for each woman predicted her children's BMI and odds ratio (OR) of being overweight or obese (BMI≥85th percentile) at a mean age of 11.9 years, using a within-family design. For every additional kg of pregnancy weight gain, childhood BMI increased by 0.0220 (95% CI 0.0134–0.0306, p<0.0001) and the OR of overweight/obesity increased by 1.007 (CI 1.003–1.012, p = 0.0008). Variations in pregnancy weight gain accounted for a 0.43 kg/m2 difference in childhood BMI. After adjustment for birth weight, the association of pregnancy weight gain with childhood BMI was attenuated but remained statistically significant (0.0143 kg/m2 per kg of pregnancy weight gain, CI 0.0057–0.0229, p = 0.0007).
Conclusions
High pregnancy weight gain is associated with increased body weight of the offspring in childhood, and this effect is only partially mediated through higher birth weight. Translation of these findings to public health obesity prevention requires additional study.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Childhood obesity has become a worldwide epidemic. For example, in the United States, the number of obese children has more than doubled in the past 30 years. 7% of American children aged 6–11 years were obese in 1980, compared to nearly 18% in 2010. Because of the rising levels of obesity, the current generation of children may have a shorter life span than their parents for the first time in 200 years.
Childhood obesity has both immediate and long-term effects on health. The initial problems are usually psychological. Obese children often experience discrimination, leading to low self-esteem and depression. Their physical health also suffers. They are more likely to be at risk of cardiovascular disease from high cholesterol and high blood pressure. They may also develop pre-diabetes or diabetes type II. In the long-term, obese children tend to become obese adults, putting them at risk of premature death from stroke, heart disease, or cancer.
There are many factors that lead to childhood obesity and they often act in combination. A major risk factor, especially for younger children, is having at least one obese parent. The challenge lies in unravelling the complex links between the genetic and environmental factors that are likely to be involved.
Why Was This Study Done?
Several studies have shown that a child's weight is influenced by his/her mother's weight before pregnancy and her weight gain during pregnancy. An obese mother, or a mother who puts on more pregnancy weight than average, is more likely to have an obese child.
One explanation for the effects of pregnancy weight gain is that the mother's overeating directly affects the baby's development. It may change the baby's brain and metabolism in such a way as to increase the child's long-term risk of obesity. Animal studies have confirmed that the offspring of overfed rats show these kinds of physiological changes. However, another possible explanation is that mother and baby share a similar genetic make-up and environment so that a child becomes obese from inheriting genetic risk factors, and growing up in a household where being overweight is the norm.
The studies in humans that have been carried out to date have not been able to distinguish between these explanations. Some have given conflicting results. The aim of this study was therefore to look for evidence of links between pregnancy weight gain and children's weight, using an approach that would separate the impact of genetic and environmental factors from a direct effect on the developing baby.
What Did the Researchers Do and Find?
The researchers examined data from the population of the US state of Arkansas recorded between 2003 and 2011. They looked at the health records of over 42,000 women who had given birth to more than one child during this period. This gave them information about how much weight the women had gained during each of their pregnancies. The researchers also looked at the school records of the children, over 91,000 in total, which included the children's body mass index (BMI, which factors in both height and weight). They analyzed the data to see if there was a link between the mothers' pregnancy weight gain and the child's BMI at around 12 years of age. Most importantly, they looked at these links within families, comparing children born to the same mother. The rationale for this approach was that these children would share a similar genetic make-up and would have grown up in similar environments. By taking genetics and environment into account in this manner, any remaining evidence of an impact of pregnancy weight gain on the children's BMI would have to be explained by other factors.
The results showed that the amount of weight each mother gained in pregnancy predicted her children's BMI and the likelihood of her children being overweight or obese. For every additional kg the mother gained during pregnancy, the children's BMI increased by 0.022. The children of mothers who put on the most weight had a BMI that was on average 0.43 higher than the children whose mothers had put on the least weight.
The study leaves some questions unanswered, including whether the mother's weight before pregnancy makes a difference to their children's BMI. The researchers were not able to obtain these measurements, nor the weight of the fathers. There may have also been other factors that weren't measured that might explain the links that were found.
What Do These Findings Mean?
This study shows that mothers who gain excessive weight during pregnancy increase the risk of their child becoming obese. This appears to be partly due to a direct effect on the developing baby.
These results represent a significant public health concern, even though the impact on an individual basis is relatively small. They could contribute to several hundred thousand cases of childhood obesity worldwide. Importantly, they also suggest that some cases could be prevented by measures to limit excessive weight gain during pregnancy. Such an approach could prove effective, as most mothers will not want to damage their child's health, and might therefore be highly motivated to change their behavior. However, because inadequate weight gain during pregnancy can also adversely affect the developing fetus, it will be essential for women to receive clear information about what constitutes optimal weight gain during pregnancy.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001521.
The US Centers for Disease Control and Prevention provide Childhood Obesity Facts
The UK National Health Service article “How much weight will I put on during my pregnancy?” provides information on pregnancy and weight gain and links to related resources
doi:10.1371/journal.pmed.1001521
PMCID: PMC3794857  PMID: 24130460
15.  Changes in CVD risk factors in the activity counseling trial 
Primary care facilities may be a natural setting for delivering interventions that focus on behaviors that improve cardiovascular disease (CVD) risk factors. The purpose of this study was to examine the 24-month effects of the Activity Counseling Trial (ACT) on CVD risk factors, to examine whether changes in CVD risk factors differed according to baseline risk factor status, and to examine whether changes in fitness were associated with changes in CVD risk factors. ACT was a 24-month multicenter randomized controlled trial to increase physical activity. Participants were 874 inactive men and women aged 35–74 years. Participants were randomly assigned to one of three arms that varied by level of counseling, intensity, and resource requirements. Because there were no significant differences in change over time between arms on any of the CVD risk factors examined, all arms were combined, and the effects of time, independent of arm, were examined separately for men and women. Time × Baseline risk factor status interactions examined whether changes in CVD risk factors differed according to baseline risk factor status. Significant improvements in total cholesterol, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol, the ratio of total cholesterol to HDL-C, and triglycerides were seen in both men and women who had high (or low for HDL-C) baseline levels of risk factors, whereas significant improvements in diastolic blood pressure were seen only in those men with high baseline levels. There were no improvements in any risk factors among participants with normal baseline levels. Changes in fitness were associated with changes in a number of CVD risk factors. However, most relationships disappeared after controlling for changes in body weight. Improvements in lipids from the ACT interventions could reduce the risk of coronary heart disease in people with already high levels of lipids by 16%–26% in men and 11%–16% in women. Interventions that can be implemented in health care settings nationwide and result in meaningful population-wide changes in CVD risk factors are needed. The ACT physical activity interventions produced substantial improvements among men and women with elevated CVD risk factors.
doi:10.2147/IJGM.S15686
PMCID: PMC3048340  PMID: 21403793
primary care counseling; cardiovascular disease risk factors; physical activity; fitness; behavioral intervention
16.  Trends in Prevalence of Dyslipidaemias and the Risk of Mortality in Lithuanian Urban Population Aged 45–64 in Relation to the Presence of the Dyslipidaemias and the Other Cardiovascular Risk Factors 
PLoS ONE  2014;9(6):e100158.
The aim of this study was to provide reliable information on dyslipidaemias, to estimate the trend of the prevalence of dyslipidaemias and other selected cardiovascular disease (CVD) risk factors at population level, and to evaluate the risk of all-cause and CVD mortality in relation to presence of mixed dyslipidaemias and other CVD risk factors.
Methods
Data from the five surveys (1983–2008) are presented. A random sample of 9,209 subjects aged 45–64 was selected for statistical analysis. During follow-up there were 1653 death cases from any cause, 864 deaths from CVD. Estimates of hazard ratios (HR) and 95% confidence intervals (CI) were based on the multivariate Cox proportional hazards regression for all-cause mortality and CVD mortality.
Results
During 25 year period the prevalence of normal total cholesterol level (<5.2 mmol/L) significantly increased only in women; triglycerides and high density lipoprotein (HDL) cholesterol did not change in men and women. Findings in our longitudinal study showed that in men and women mixed dyslipidaemias (HDL cholesterol <1.03 mmol/L plus triglycerides ≥1.70 mmol/L) significantly increased the risk for all-cause and CVD mortality (respectively in men HR = 1.30; HR = 1.15, in women HR = 1.83; HR = 2.13). These mixed dyslipidaemia combinations combination with the other risk factors such as arterial hypertension, high fasting glucose level increased all-cause and CVD mortality risk in men and women; while, these mixed dyslipidaemias plus smoking increased all-cause and CVD mortality risk only in men compared to never smokers without these dyslipidaemias (respectively HR = 1.89; HR = 1.92); and these dyslipidaemias plus obesity increased all-cause and CVD mortality risk in women (respectively HR = 2.25; HR = 2.39) and CVD mortality risk in men (HR = 1.72), as compared to responders without obesity and these dyslipidaemias.
Conclusion
Mixed dyslipidaemias (reduced HDL cholesterol plus elevated triglycerides) significantly increased the risk for all-cause and CVD mortality in this Lithuanian population aged 45–64 years.
doi:10.1371/journal.pone.0100158
PMCID: PMC4067295  PMID: 24955583
17.  Anthropometric measurements of general and central obesity and the prediction of cardiovascular disease risk in women: a cross-sectional study 
BMJ Open  2014;4(2):e004138.
Objectives
It is important to ascertain which anthropometric measurements of obesity, general or central, are better predictors of cardiovascular disease (CVD) risk in women. 10-year CVD risk was calculated from the Framingham risk score model, SCORE risk chart for high-risk regions, general CVD and simplified general CVD risk score models. Increase in CVD risk associated with 1 SD increment in each anthropometric measurement above the mean was calculated, and the diagnostic utility of obesity measures in identifying participants with increased likelihood of being above the treatment threshold was assessed.
Design
Cross-sectional data from the National Heart Foundation Risk Factor Prevalence Study.
Setting
Population-based survey in Australia.
Participants
4487 women aged 20–69 years without heart disease, diabetes or stroke.
Outcome measures
Anthropometric obesity measures that demonstrated the greatest increase in CVD risk as a result of incremental change, 1 SD above the mean, and obesity measures that had the greatest diagnostic utility in identifying participants above the respective treatment thresholds of various risk score models.
Results
Waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-stature ratio had larger effects on increased CVD risk compared with body mass index (BMI). These central obesity measures also had higher sensitivity and specificity in identifying women above and below the 20% treatment threshold than BMI. Central obesity measures also recorded better correlations with CVD risk compared with general obesity measures. WC and WHR were found to be significant and independent predictors of CVD risk, as indicated by the high area under the receiver operating characteristic curves (>0.76), after controlling for BMI in the simplified general CVD risk score model.
Conclusions
Central obesity measures are better predictors of CVD risk compared with general obesity measures in women. It is equally important to maintain a healthy weight and to prevent central obesity concurrently.
doi:10.1136/bmjopen-2013-004138
PMCID: PMC3918987  PMID: 24503301
Public Health; Epidemiology
18.  Nonfasting triglycerides and risk of cardiovascular death in men and women from the Norwegian Counties Study 
European Journal of Epidemiology  2010;25(11):789-798.
The association between nonfasting triglycerides and cardiovascular disease (CVD) has recently been actualized. The aim of the present study was to investigate nonfasting triglycerides as a predictor of CVD mortality in men and women. A total of 86,261 participants in the Norwegian Counties Study 1974–2007, initially aged 20–50 years and free of CVD were included. We estimated hazard ratios (HRs) for deaths from CVD, ischemic heart disease (IHD), stroke and all causes by level of nonfasting triglycerides. Mean follow-up was 27.0 years. A total of 9,528 men died (3,620 from CVD, 2,408 IHD, 543 stroke), and totally 5,267 women died (1,296 CVD, 626 IHD, 360 stroke). After adjustment for CVD risk factors other than HDL-cholesterol, the HRs (95% CI) per 1 mmol/l increase in nonfasting triglycerides were 1.16 (1.13–1.20), 1.20 (1.14–1.27), 1.26 (1.19–1.34) and 1.09 (0.96–1.23) for all cause mortality, CVD, IHD, and stroke mortality in women. Corresponding figures in men were 1.03 (1.01–1.04), 1.03 (1.00–1.05), 1.03 (1.00–1.06) and 0.99 (0.92–1.07). In a subsample where HDL-cholesterol was measured (n = 40,144), the association between CVD mortality and triglycerides observed in women disappeared after adjustment for HDL-cholesterol. In a model including the Framingham CHD risk score the effect of triglycerides disappeared in both men and women. In conclusion, nonfasting triglycerides were associated with increased risk of CVD death for both women and men. Adjustment for major cardiovascular risk factors, however, attenuated the effect. Nonfasting triglycerides added no predictive information on CVD mortality beyond the Framingham CHD risk score in men and women.
doi:10.1007/s10654-010-9501-1
PMCID: PMC2991549  PMID: 20890636
Triglycerides; Cardiovascular disease; Mortality; Nonfasting; Cohort study
19.  Erectile Dysfunction Severity as a Risk Marker for Cardiovascular Disease Hospitalisation and All-Cause Mortality: A Prospective Cohort Study 
PLoS Medicine  2013;10(1):e1001372.
In a prospective Australian population-based study linking questionnaire data from 2006–2009 with hospitalisation and death data to June 2010 for 95,038 men aged ≥45 years, Banks and colleagues found that more severe erectile dysfunction was associated with higher risk of cardiovascular disease.
Background
Erectile dysfunction is an emerging risk marker for future cardiovascular disease (CVD) events; however, evidence on dose response and specific CVD outcomes is limited. This study investigates the relationship between severity of erectile dysfunction and specific CVD outcomes.
Methods and Findings
We conducted a prospective population-based Australian study (the 45 and Up Study) linking questionnaire data from 2006–2009 with hospitalisation and death data to 30 June and 31 Dec 2010 respectively for 95,038 men aged ≥45 y. Cox proportional hazards models were used to examine the relationship of reported severity of erectile dysfunction to all-cause mortality and first CVD-related hospitalisation since baseline in men with and without previous CVD, adjusting for age, smoking, alcohol consumption, marital status, income, education, physical activity, body mass index, diabetes, and hypertension and/or hypercholesterolaemia treatment. There were 7,855 incident admissions for CVD and 2,304 deaths during follow-up (mean time from recruitment, 2.2 y for CVD admission and 2.8 y for mortality). Risks of CVD and death increased steadily with severity of erectile dysfunction. Among men without previous CVD, those with severe versus no erectile dysfunction had significantly increased risks of ischaemic heart disease (adjusted relative risk [RR] = 1.60, 95% CI 1.31–1.95), heart failure (8.00, 2.64–24.2), peripheral vascular disease (1.92, 1.12–3.29), “other” CVD (1.26, 1.05–1.51), all CVD combined (1.35, 1.19–1.53), and all-cause mortality (1.93, 1.52–2.44). For men with previous CVD, corresponding RRs (95% CI) were 1.70 (1.46–1.98), 4.40 (2.64–7.33), 2.46 (1.63–3.70), 1.40 (1.21–1.63), 1.64 (1.48–1.81), and 2.37 (1.87–3.01), respectively. Among men without previous CVD, RRs of more specific CVDs increased significantly with severe versus no erectile dysfunction, including acute myocardial infarction (1.66, 1.22–2.26), atrioventricular and left bundle branch block (6.62, 1.86–23.56), and (peripheral) atherosclerosis (2.47, 1.18–5.15), with no significant difference in risk for conditions such as primary hypertension (0.61, 0.16–2.35) and intracerebral haemorrhage (0.78, 0.20–2.97).
Conclusions
These findings give support for CVD risk assessment in men with erectile dysfunction who have not already undergone assessment. The utility of erectile dysfunction as a clinical risk prediction tool requires specific testing.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Erectile dysfunction is the medical term used when a man is unable to achieve or sustain an erection of his penis suitable for sexual intercourse. Although a sensitive topic that can cause much embarrassment and distress, erectile dysfunction is very common, with an estimated 40% of men over the age of 40 years experiencing frequent or occasional difficulties. The most common causes of erectile dysfunction are medications, chronic illnesses such as diabetes, and drinking too much alcohol. Stress and mental health problems can also cause or worsen erectile dysfunction. There is also increasing evidence that erectile dysfunction may actually be a symptom of cardiovascular disease—a leading cause of death worldwide—as erectile dysfunction could indicate a problem with blood vessels or poor blood flow commonly associated with cardiovascular disease.
Why Was This Study Done?
Although previous studies have suggested that erectile dysfunction can serve as a marker for cardiovascular disease in men not previously diagnosed with the condition, few studies to date have investigated whether erectile dysfunction could also indicate worsening disease in men already diagnosed with cardiovascular disease. In addition, previous studies have typically been small and have not graded the severity of erectile dysfunction or investigated the specific types of cardiovascular disease associated with erectile dysfunction. In this large study conducted in Australia, the researchers investigated the relationship of the severity of erectile dysfunction with a range of cardiovascular disease outcomes among men with and without a previous diagnosis of cardiovascular disease.
What Did the Researchers Do and Find?
The researchers used information from the established 45 and Up Study, a large cohort study that includes 123,775 men aged 45 and over, selected at random from the general population of New South Wales, a large region of Australia. A total of 95,038 men were included in this analysis. The male participants completed a postal questionnaire that included a question on erectile functioning, which allowed the researchers to define erectile dysfunction as none, mild, moderate, or severe. Using information captured in the New South Wales Admitted Patient Data Collection—a complete record of all public and private hospital admissions, including the reasons for admission and the clinical diagnosis—and the government death register, the researchers were able to determine health outcomes of all study participants. They then used a statistical model to estimate hospital admissions for cardiovascular disease events for different levels of erectile dysfunction.
The researchers found that the rates of severe erectile dysfunction among study participants were 2.2% for men aged 45–54 years, 6.8% for men aged 55–64 years, 20.2% for men aged 65–74 years, 50.0% for men aged 75–84 years, and 75.4% for men aged 85 years and over. During the study period, the researchers recorded 7,855 hospital admissions related to cardiovascular disease and 2,304 deaths. The researchers found that among men without previous cardiovascular disease, those with severe erectile dysfunction were more likely to develop ischemic heart disease (risk 1.60), heart failure (risk 8.00), peripheral vascular disease (risk 1.92), and other causes of cardiovascular disease (risk 1.26) than men without erectile dysfunction. The risks of heart attacks and heart conduction problems were also increased (1.66 and 6.62, respectively). Furthermore, the combined risk of all cardiovascular disease outcomes was 1.35, and the overall risk of death was also higher (risk 1.93) in these men. The researchers found that these increased risks were similar in men with erectile dysfunction who had previously been diagnosed with cardiovascular disease.
What Do These Findings Mean?
These findings suggest that compared to men without erectile dysfunction, there is an increasing risk of ischemic heart disease, peripheral vascular disease, and death from all causes in those with increasing degrees of severity of erectile dysfunction. The authors emphasize that erectile dysfunction is a risk marker for cardiovascular disease, not a risk factor that causes cardiovascular disease. These findings add to previous studies and highlight the need to consider erectile dysfunction in relation to the risk of different types of cardiovascular disease, including heart failure and heart conduction disorders. However, the study's reliance on the answer to a single self-assessed question on erectile functioning limits the findings. Nevertheless, these findings provide useful information for clinicians: men with erectile dysfunction are at higher risk of cardiovascular disease, and the worse the erectile dysfunction, the higher the risk of cardiovascular disease. Men with erectile dysfunction, even at mild or moderate levels, should be screened and treated for cardiovascular disease accordingly.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001372.
Wikipedia defines erectile dysfunction (note that Wikipedia is a free online encyclopedia that anyone can edit)
MedlinePlus also has some useful patient information on erectile dysfunction
The Mayo Clinic has patient-friendly information on the causes of, and treatments for, erectile dysfunction, and also includes information on the link with cardiovascular disease
The National Heart Foundation of Australia provides information for health professionals, patients, and the general public about how to prevent and manage cardiovascular disease, including assessment and management of cardiovascular disease risk
doi:10.1371/journal.pmed.1001372
PMCID: PMC3558249  PMID: 23382654
20.  Excess Cardiovascular Risk Burden in Jamaican Women Does Not Influence Predicted 10-Year CVD Risk Profiles of Jamaica Adults: An Analysis of the 2007/08 Jamaica Health and Lifestyle Survey 
PLoS ONE  2013;8(6):e66625.
Background
Black Caribbean women have a higher burden of cardiovascular disease (CVD) risk factors than their male counterparts. Whether this results in a difference in incident cardiovascular events is unknown. The aim of this study was to estimate the 10 year World Health Organization/International Society for Hypertension (WHO/ISH) CVD risk score for Jamaica and explore the effect of sex as well as obesity, physical activity and socioeconomic status on these estimates.
Methods and Findings
Data from 40–74 year old participants in the 2007/08 Jamaica Health and Lifestyle Survey were used. Trained interviewers administered questionnaires and measured anthropometrics, blood pressure, fasting glucose and cholesterol. Education and occupation were used to assess socioeconomic status. The Americas B tables were used to estimate the WHO/ISH 10 year CVD risk scores for the population. Weighted prevalence estimates were calculated. Data from 1,432 (450 men, 982 women) participants were analysed, after excluding those with self-reported heart attack and stroke. The women had a higher prevalence of diabetes (19%W;12%M), hypertension (49%W;47%M), hypercholesterolemia (25%W;11%M), obesity (46%W;15%M) and physical inactivity (59%W;29%M). More men smoked (6%W;31%M). There was good agreement between the 10-year cardiovascular risk estimates whether or not cholesterol measurements were utilized for calculation (kappa –0.61). While 90% had a 10 year WHO/ISH CVD risk of less than 10%, approximately 2% of the population or 14,000 persons had a 10 year WHO/ISH CVD risk of ≥30%. As expected CVD risk increased with age but there was no sex difference in CVD risk distribution despite women having a greater risk factor burden. Women with low socioeconomic status had the most adverse CVD risk profile.
Conclusion
Despite women having a higher prevalence of CVD risk factors there was no sex difference in 10-year WHO/ISH CVD risk in Jamaican adults.
doi:10.1371/journal.pone.0066625
PMCID: PMC3689813  PMID: 23805252
21.  Chronic Kidney Disease as a Predictor of Cardiovascular Disease (From the Framingham Heart Study) 
Chronic kidney disease (CKD) is a risk factor for cardiovascular disease (CVD), although shared risk factors may mediate much of the association. We related CKD and CVD in the setting of specific CVD risk factors and determined whether more advanced CKD was a CVD risk equivalent. The Framingham Heart Study original cohort (n=2471, mean age 68 years, 58.9% women) was studied. Glomerular filtration rate (eGFR) was estimated using the simplified Modification of Diet in Renal Disease Study equation. CKD was defined as eGFR < 59 mL/min per 1.73 m2 (women) and < 64 (men) and Stage 3b CKD defined as eGFR 30-44 (women) and 30-50 (men). Cox Proportional Hazard models adjusting for CVD risk factors were used to relate CKD to CVD. We tested for effect modification by CVD risk factors. Overall, 23.2% of the study sample had CKD (n=574; mean eGFR 50 mL/min per 1.73 m2) and 5.3% had Stage 3b CKD (n=131; mean eGFR 42 mL/min per 1.73 m2). In multivariable models (mean follow-up time 16 years), Stage 3 CKD was marginally associated with CVD (HR=1.17, 95% CI 0.99-1.38, p=0.06), whereas Stage 3b CKD was associated with CVD [HR=1.41, 95% CI 1.05-1.91, p=0.02]. Upon testing CVD risk equivalency, the risk of CVD for Stage 3b CKD among participants with prior CVD was significantly lower as compared to participants with prior CVD and no Stage 3b CKD (age- and sex-adjusted HR for CVD = 0.66 [95% CI 0.47 to 0.91], p=0.01). Low HDL modified the association between CKD and CVD (p-value=0.004 for interaction). Stage 3b CKD is associated with CVD but is not a CVD risk equivalent. In conclusion, CVD risk in the setting of CKD is higher in the setting of low HDL cholesterol.
doi:10.1016/j.amjcard.2008.02.095
PMCID: PMC2517213  PMID: 18572034
22.  Lifetime Risk and Years Lived Free of Total Cardiovascular Disease 
Context
Estimates of lifetime risk (LTR) for total cardiovascular disease (tCVD) may provide projections of the future population burden of cardiovascular disease and may assist in clinician-patient risk communication. To date, no LTR estimates of tCVD have been reported.
Objective
To calculate LTR estimates of tCVD by index age [45, 55, 65, 75 years(y)] and risk factor strata and to estimate years lived free of CVD across risk factor strata.
Design, Setting, and Participants
Pooled survival analysis of up to 905,115 person-years of data from 1964 through 2008 from 5 NHLBI-funded community-based cohorts: Framingham Heart Study, Framingham Offspring Study, Atherosclerosis Risk in Communities Study, Chicago Heart Association Detection Project in Industry Study and Cardiovascular Health Study.
Participants
All participants free of CVD at baseline with risk factor data (blood pressure (BP), total cholesterol (TC), diabetes and smoking status) and tCVD outcome data
Outcome Measures
Any tCVD event (including fatal and non-fatal coronary heart disease, all forms of stroke, congestive heart failure and other CVD deaths)
Results
At an index age of 45y, overall LTR for tCVD was 60.3% (95% CI, 59.3 to 61.2) for men and 55.6% (95% CI, 54.5 to 56.7) for women. Men had higher LTR estimates than women across all index ages. At index ages 55 and 65y, men and women with ≥1 elevated risk factor (BP 140-149/90-99 mmHg or TC 200-239 mg/dL but no diabetes or smoking), or 1, or ≥ 2 major risk factors (BP ≥ 160/100mmHg or on treatment; TC ≥ 240mg/dL or on treatment, diabetes mellitus, or current smoking) had LTR estimates to age 95y that exceeded 50%. Despite an optimal risk factor profile (BP < 120/80 mmHg, TC < 180 mg/dL, and no smoking or diabetes) men and women at an index age of 55y had LTR for total CVD to age 85y > 40% and 30% respectively. Compared with participants with ≥ 2 major risk factors, those with an optimal risk factor profile lived up to 14y longer free of tCVD.
Conclusions
LTR estimates for tCVD are high (>30%) for all individuals, even those with optimal risk factors in middle age. However, maintenance of optimal risk factor levels in middle age is associated with substantially longer morbidity-free survival.
doi:10.1001/jama.2012.14312
PMCID: PMC3748966  PMID: 23117780
Lifetime Risk; Cardiovascular Disease; Compression of Morbidity
23.  Association between Class III Obesity (BMI of 40–59 kg/m2) and Mortality: A Pooled Analysis of 20 Prospective Studies 
PLoS Medicine  2014;11(7):e1001673.
In a pooled analysis of 20 prospective studies, Cari Kitahara and colleagues find that class III obesity (BMI of 40–59) is associated with excess rates of total mortality, particularly due to heart disease, cancer, and diabetes.
Please see later in the article for the Editors' Summary
Background
The prevalence of class III obesity (body mass index [BMI]≥40 kg/m2) has increased dramatically in several countries and currently affects 6% of adults in the US, with uncertain impact on the risks of illness and death. Using data from a large pooled study, we evaluated the risk of death, overall and due to a wide range of causes, and years of life expectancy lost associated with class III obesity.
Methods and Findings
In a pooled analysis of 20 prospective studies from the United States, Sweden, and Australia, we estimated sex- and age-adjusted total and cause-specific mortality rates (deaths per 100,000 persons per year) and multivariable-adjusted hazard ratios for adults, aged 19–83 y at baseline, classified as obese class III (BMI 40.0–59.9 kg/m2) compared with those classified as normal weight (BMI 18.5–24.9 kg/m2). Participants reporting ever smoking cigarettes or a history of chronic disease (heart disease, cancer, stroke, or emphysema) on baseline questionnaires were excluded. Among 9,564 class III obesity participants, mortality rates were 856.0 in men and 663.0 in women during the study period (1976–2009). Among 304,011 normal-weight participants, rates were 346.7 and 280.5 in men and women, respectively. Deaths from heart disease contributed largely to the excess rates in the class III obesity group (rate differences = 238.9 and 132.8 in men and women, respectively), followed by deaths from cancer (rate differences = 36.7 and 62.3 in men and women, respectively) and diabetes (rate differences = 51.2 and 29.2 in men and women, respectively). Within the class III obesity range, multivariable-adjusted hazard ratios for total deaths and deaths due to heart disease, cancer, diabetes, nephritis/nephrotic syndrome/nephrosis, chronic lower respiratory disease, and influenza/pneumonia increased with increasing BMI. Compared with normal-weight BMI, a BMI of 40–44.9, 45–49.9, 50–54.9, and 55–59.9 kg/m2 was associated with an estimated 6.5 (95% CI: 5.7–7.3), 8.9 (95% CI: 7.4–10.4), 9.8 (95% CI: 7.4–12.2), and 13.7 (95% CI: 10.5–16.9) y of life lost. A limitation was that BMI was mainly ascertained by self-report.
Conclusions
Class III obesity is associated with substantially elevated rates of total mortality, with most of the excess deaths due to heart disease, cancer, and diabetes, and major reductions in life expectancy compared with normal weight.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
The number of obese people (individuals with an excessive amount of body fat) is increasing rapidly in many countries. Worldwide, according to the Global Burden of Disease Study 2013, more than a third of all adults are now overweight or obese. Obesity is defined as having a body mass index (BMI, an indicator of body fat calculated by dividing a person's weight in kilograms by their height in meters squared) of more than 30 kg/m2 (a 183-cm [6-ft] tall man who weighs more than 100 kg [221 lbs] is obese). Compared to people with a healthy weight (a BMI between 18.5 and 24.9 kg/m2), overweight and obese individuals (who have a BMI between 25.0 and 29.9 kg/m2 and a BMI of 30 kg/m2 or more, respectively) have an increased risk of developing diabetes, heart disease, stroke, and some cancers, and tend to die younger. Because people become unhealthily fat by consuming food and drink that contains more energy (kilocalories) than they need for their daily activities, obesity can be prevented or treated by eating less food and by increasing physical activity.
Why Was This Study Done?
Class III obesity (extreme, or morbid, obesity), which is defined as a BMI of more than 40 kg/m2, is emerging as a major public health problem in several high-income countries. In the US, for example, 6% of adults are now morbidly obese. Because extreme obesity used to be relatively uncommon, little is known about the burden of disease, including total and cause-specific mortality (death) rates, among individuals with class III obesity. Before we can prevent and treat class III obesity effectively, we need a better understanding of the health risks associated with this condition. In this pooled analysis of prospective cohort studies, the researchers evaluate the risk of total and cause-specific death and the years of life lost associated with class III obesity. A pooled analysis analyzes the data from several studies as if the data came from one large study; prospective cohort studies record the characteristics of a group of participants at baseline and follow them to see which individuals develop a specific condition.
What Did the Researchers Do and Find?
The researchers included 20 prospective (mainly US) cohort studies from the National Cancer Institute Cohort Consortium (a partnership that studies cancer by undertaking large-scale collaborations) in their pooled analysis. After excluding individuals who had ever smoked and people with a history of chronic disease, the analysis included 9,564 adults who were classified as class III obese based on self-reported height and weight at baseline and 304,011 normal-weight adults. Among the participants with class III obesity, mortality rates (deaths per 100,000 persons per year) during the 30-year study period were 856.0 and 663.0 in men and women, respectively, whereas the mortality rates among normal-weight men and women were 346.7 and 280.5, respectively. Heart disease was the major contributor to the excess death rate among individuals with class III obesity, followed by cancer and diabetes. Statistical analyses of the pooled data indicate that the risk of all-cause death and death due to heart disease, cancer, diabetes, and several other diseases increased with increasing BMI. Finally, compared with having a normal weight, having a BMI between 40 and 59 kg/m2 resulted in an estimated loss of 6.5 to 13.7 years of life.
What Do These Findings Mean?
These findings indicate that class III obesity is associated with a substantially increased rate of death. Notably, this death rate increase is similar to the increase associated with smoking among normal-weight people. The findings also suggest that heart disease, cancer, and diabetes are responsible for most of the excess deaths among people with class III obesity and that having class III obesity results in major reductions in life expectancy. Importantly, the number of years of life lost continues to increase for BMI values above 50 kg/m2, and beyond this point, the loss of life expectancy exceeds that associated with smoking among normal-weight people. The accuracy of these findings is limited by the use of self-reported height and weight measurements to calculate BMI and by the use of BMI as the sole measure of obesity. Moreover, these findings may not be generalizable to all populations. Nevertheless, these findings highlight the need to develop more effective interventions to combat the growing public health problem of class III obesity.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001673.
The US Centers for Disease Control and Prevention provides information on all aspects of overweight and obesity (in English and Spanish)
The World Health Organization provides information on obesity (in several languages); Malri's story describes the health risks faced by an obese child
The UK National Health Service Choices website provides information about obesity, including a personal story about losing weight
The Global Burden of Disease Study website provides the latest details about global obesity trends
The US Department of Agriculture's ChooseMyPlate.gov website provides a personal healthy eating plan; the Weight-Control Information Network is an information service provided for the general public and health professionals by the US National Institute of Diabetes and Digestive and Kidney Diseases (in English and Spanish)
MedlinePlus provides links to other sources of information on obesity (in English and Spanish)
doi:10.1371/journal.pmed.1001673
PMCID: PMC4087039  PMID: 25003901
24.  Living healthier for longer: Comparative effects of three heart-healthy behaviors on life expectancy with and without cardiovascular disease 
BMC Public Health  2009;9:487.
Background
Non-smoking, having a normal weight and increased levels of physical activity are perhaps the three key factors for preventing cardiovascular disease (CVD). However, the relative effects of these factors on healthy longevity have not been well described. We aimed to calculate and compare the effects of non-smoking, normal weight and physical activity in middle-aged populations on life expectancy with and without cardiovascular disease.
Methods
Using multi-state life tables and data from the Framingham Heart Study (n = 4634) we calculated the effects of three heart healthy behaviours among populations aged 50 years and over on life expectancy with and without cardiovascular disease. For the life table calculations, we used hazard ratios for 3 transitions (No CVD to CVD, no CVD to death, and CVD to death) by health behaviour category, and adjusted for age, sex, and potential confounders.
Results
High levels of physical activity, never smoking (men), and normal weight were each associated with 20-40% lower risks of developing CVD as compared to low physical activity, current smoking and obesity, respectively. Never smoking and high levels of physical activity reduced the risks of dying in those with and without a history of CVD, but normal weight did not. Never-smoking was associated with the largest gains in total life expectancy (4.3 years, men, 4.1 years, women) and CVD-free life expectancy (3.8 and 3.4 years, respectively). High levels of physical activity and normal weight were associated with lesser gains in total life expectancy (3.5 years, men and 3.4 years, women, and 1.3 years, men and 1.0 year women, respectively), and slightly lesser gains in CVD-free life expectancy (3.0 years, men and 3.1 years, women, and 3.1 years men and 2.9 years women, respectively). Normal weight was the only behaviour associated with a reduction in the number of years lived with CVD (1.8 years, men and 1.9 years, women).
Conclusions
Achieving high levels of physical activity, normal weight, and never smoking, are effective ways to prevent cardiovascular disease and to extend total life expectancy and the number of years lived free of CVD. Increasing the prevalence of normal weight could further reduce the time spent with CVD in the population.
doi:10.1186/1471-2458-9-487
PMCID: PMC2813239  PMID: 20034381
25.  Lipid measures for prediction of incident cardiovascular disease in diabetic and non-diabetic adults: results of the 8.6 years follow-up of a population based cohort study 
Background
Diabetes is a strong risk factor for cardiovascular disease (CVD).The relative role of various lipid measures in determining CVD risk in diabetic patients is still a subject of debate. We aimed to compare performance of different lipid measures as predictors of CVD using discrimination and fitting characteristics in individuals with and without diabetes mellitus from a Middle East Caucasian population.
Methods
The study population consisted of 1021 diabetic (men = 413, women = 608) and 5310 non-diabetic (men = 2317, women = 2993) subjects, aged ≥ 30 years, free of CVD at baseline. The adjusted hazard ratios (HRs) for CVD were calculated for a 1 standard deviation (SD) change in total cholesterol (TC), log-transformed triglyceride (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), non-HDL-C, TC/HDL-C and log-transformed TG/HDL-C using Cox proportional regression analysis. Incident CVD was ascertained over a median of 8.6 years of follow-up.
Results
A total of 189 (men = 91, women = 98) and 263(men = 169, women = 94) CVD events occurred, in diabetic and non-diabetic population, respectively. The risk factor adjusted HRs to predict CVD, except for HDL-C, TG and TG/HDL-C, were significant for all lipid measures in diabetic males and were 1.39, 1.45, 1.36 and 1.16 for TC, LDL-C, non- HDL-C and TC/HDL-C respectively. In diabetic women, using multivariate analysis, only TC/HDL-C had significant risk [adjusted HR1.31(1.10-1.57)].Among non-diabetic men, all lipid measures, except for TG, were independent predictors for CVD however; a 1 SD increase in HDL-C significantly decreased the risk of CVD [adjusted HR 0.83(0.70-0.97)].In non-diabetic women, TC, LDL-C, non-HDL-C and TG were independent predictors.
There was no difference in the discriminatory power of different lipid measures to predict incident CVD in the risk factor adjusted models, in either sex of diabetic and non-diabetic population.
Conclusion
Our data according to important test performance characteristics provided evidence based support for WHO recommendation that along with other CVD risk factors serum TC vs. LDL-C, non-HDL-C and TC/HDL-C is a reasonable lipid measure to predict incident CVD among diabetic men. Importantly, HDL-C did not have a protective effect for incident CVD among diabetic population; given that the HDL-C had a protective effect only among non- diabetic men.
doi:10.1186/1476-511X-9-6
PMCID: PMC2835707  PMID: 20096127

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