Target organ damage and incident type 2 diabetes mellitus: the Strong Heart Study
© The Author(s) 2017
Received: 13 March 2017
Accepted: 28 April 2017
Published: 12 May 2017
Recent analyses in a registry of hypertensive patients suggested that preceding left ventricular (LV) hypertrophy (LVH) and/or carotid atherosclerosis are associated with incident type 2 diabetes, independent of confounders. We assess the relation between prevalent cardio-renal target organ damage (TOD) and subsequent incident type 2 diabetes in a population-based study with high prevalence of obesity.
We selected 2887 non-diabetic participants from two cohorts of the Strong Heart Study (SHS). Clinical exam, laboratory tests and echocardiograms were performed. Adjudicated TODs were LVH, left atrium (LA) dilatation, and high urine albumin/creatinine ratio (UACR). Multivariable logistic regression models were used to identify variables responsible for the association between initial TODs and incident diabetes at 4-year follow-up (FU).
After 4 years, 297 new cases of diabetes (10%) were identified, 216 of whom exhibited baseline impaired fasting glucose (IFG, 73%, p < 0.0001). Participants developing type 2 diabetes exhibited higher inflammatory markers, fat-free mass and adipose mass and higher prevalence of initial LVH and LA dilatation than those without (both p < 0.04). In multivariable logistic regression, controlling for age, sex, family relatedness, presence of arterial hypertension and IFG, all three indicators of TOD predicted incident diabetes (all p < 0.01). However, the effects of TOD was offset when body fat and inflammatory markers were introduced into the model.
In this population-based study with high prevalence of obesity, TOD precedes clinical appearance of type 2 diabetes and is related to the preceding metabolic status, body composition and inflammatory status.
Trial registration Trial registration number: NCT00005134, Name of registry: Strong Heart Study, URL of registry: https://clinicaltrials.gov/ct2/show/NCT00005134, Date of registration: May 25, 2000, Date of enrolment of the first participant to the trial: September 1988
KeywordsArterial hypertension Left ventricular hypertrophy Left atrial dilatation Target organ damage Body composition Inflammation
Similar to arterial hypertension and obesity, type 2 diabetes mellitus is associated with target organ damage (TOD) [1–3]. However, the sequence between major CV risk factor and TOD has been brought into question by evidence that sometimes TOD precedes the clinical appearance of the disease that is thought to cause it. This potential reverse causation has also been postulated for arterial hypertension and for the possibility to optimally control blood pressure by therapy [4, 5].
More recently, analyses performed in the hypertensive population of the Campania Salute Network (CSN) registry demonstrated that LV hypertrophy and/or carotid atherosclerosis are predictors of incident type 2 diabetes , independent of a number of confounders, including age, metabolic syndrome, family history of diabetes, duration of hypertension, and number and type of antihypertensive medications. While in the case of hypertension, masked hypertension and non-dipping pattern due to obstructive sleep apnoea, could help explain why LV hypertrophy appears before clinical manifestation of hypertension detected in the doctor’s office, in the case of type 2 diabetes a clear explanation is more difficult. The reported temporal sequence between TOD and clinical presentation of DM was possibly attributed to risk factors both affecting the CV system and leading to type 2 diabetes, to which LV hypertrophy and/or carotid atherosclerosis may be more sensitive, potentially consistent with the postulated possibility of a vascular origin of type 2 diabetes .
At present, the generalizability of the findings of the Campagna Salute Network hypertensive registry to unselected populations cohorts has not been evaluated. Accordingly, this analysis has been designed to evaluate the relation between prevalent TOD and subsequent incident type 2 diabetes in the population of the Strong Heart Study (SHS), and to verify whether conditions associated to pre-diabetes help explain the association.
The SHS is a population-based cohort-study of CV risk factors and disease in American Indians originally from 13 communities, as extensively previously described [7, 8], with follow-up examinations of the original SHS cohort approximately 4 and 8 years after the 1st SHS exam in 1989–1992. During the 2nd exam, the SHS cohort members underwent also standard Doppler-echocardiography. The 4th SHS exam, in 2001–2003, enrolled members of large multi-generation families [Strong Heart Family Study (SHFS)], who underwent echocardiography [9, 10].
Clinical examination, laboratory tests and definitions
Detailed descriptions of the study design and methods of the SHS and SHFS have previously been reported [7–10]. Obesity was classified as BMI ≥30 kg/m2. Waist circumference was used as an indicator of central adiposity, using sex-specific cut-points . Arterial hypertension was defined by BP ≥140/90 mmHg or current antihypertensive treatment.
Fat-free mass and adipose body mass were estimated by using an RJL bioelectric impedance meter (model B14101; RJL Equipment Co.), as previously reported . Equations to estimate fat-free mass (FFM) in kg, based on total body water, had been previously validated in the American Indian population .
Fasting plasma glucose, lipid profile and other laboratory variables were measured by standard methods, as previously reported [7, 8]. Type 2 diabetes was defined as fasting glucose ≥126 mg/dL or use of antidiabetic treatment . Impaired fasting glucose (IFG) was defined as a fasting glucose >100 mg/dL , whereas fasting glucose ≤100 mg/dL was defined as normal fasting glucose (NFG).
Glomerular filtration rate (GFR) was estimated by the simplified Modification of Diet in Renal Disease formula . Urinary albumin excretion was measured on a single spot urine sample and was expressed in relation to grams of urinary creatinine (uAlb/Crea). The ratio uAlb/Crea was also categorized based on the distribution in initially non-diabetic participants in this study, using the 75th percentile of the distribution (i.e. 13 g/mg) as cut point.
Echocardiograms were performed using phased-array, commercially available echocardiographs, with M-mode, two-dimensional and Doppler capabilities, and read off line using working stations equipped with frame-grabber to measure on analog stop-frame images, as previously reported in detail [16, 17]. From left ventricular (LV) internal dimension and wall thicknesses, LV mass (LVM) was calculated using an autopsy-validated formula  and normalized by height to the allometric power of 2.7 (LVMi) . LV hypertrophy (LVH) was defined using the population specific partition values of 47.2 g/m2.7 for both men and women . In the SHS, this cut-point maximized the population risk attributable to LVH, compared to sex-specific approaches. LV geometry was assessed by relative wall thickness (RWT) normalized to an age of 46 years (RWTa), as previously suggested . LV concentricity was defined as RWTa greater than 0.41 . Analysis of reliability of echocardiographic LV mass yielded an intraclass coefficient of 0.93 in this laboratory (p < 0.001) .
LAv was normalized for height in meters raised to the second power, based on a recent evidence provided by an European epidemiologic study . From this study, the sex-specific partitions of >19.4 mL/m2 for men and >16.6 mL/m2 for women were adopted, which provide high sensitivity and specificity for detection of LA dilatation .
The outcome variable of this study was incident type 2 diabetes defined as fasting glucose ≥126 mg/dL or taking oral antidiabetic medications. Censoring for diabetes was done after 4 years (exams 3 and 5, for the SHS original cohort and for the SHFS, respectively). The markers of TOD evaluated as predictors of incident diabetes were LV hypertrophy, LA dilatation and high uAlb/Crea.
Data were analyzed using IBM-SPSS 23.0 and expressed as mean ± standard deviation or proportion in the Chi square distribution. Indicator variables were included for the Arizona, South/North Dakota and Oklahoma field centers. Because in this population, including members of the SHFS cohort, the level of family relatedness was high, we adjusted analysis for a standard kinship coefficient, based on the level of relatedness within family, as previously reported . Continuous baseline variables were compared between groups with or without incident diabetes, using 2-factor ANCOVA, adjusting for baseline glucose status (i.e. NFG or IFG), and family relatedness. Skewed variables were logarithmically transformed to be analysed with parametric statistics, and are expressed as median and interquartile range. To verify whether the markers of TOD retained their effect on incident diabetes, sequential multivariable logistic regression models were implemented for each TOD marker, to identify confounders (if any) that could help explain its association with incident type 2 diabetes. Because among the variables of interest, we found about 2% of missing values, with no variables exceeding more than 10% of missing values, multiple imputation was adopted, using the SPSS automatic imputing algorithm [25, 26].
Of the 2887 participants, 1825 presented with normal fasting glucose (NFG, 60% women) and 1062 (57% women) with impaired fasting glucose (IFG).
At the censoring time, 4 years after the initial examination, 297 new cases of type 2 diabetes (10% of the study population) were identified, 216 of whom exhibited baseline impaired fasting glucose (73%, p < 0.0001). At the initial exam, hypertension was present in 30% of the normal fasting glucose (NFG) sub-population and in 48% of participants with IFG (p < 0.0001). Even more marked was the difference in central fat distribution (55% in NGT and 74% in IFG, p < 0.0001).
The following analyses were carried out in the censored subpopulation at follow-up. Incident type 2 diabetes was associated with initial IFG, greater prevalence of obesity, substantial prevalence of central fat distribution, whereas the difference in prevalent arterial hypertension was not significant.
Clinical and echocardiographic characteristics of participants remaining non-diabetic and those developing diabetes
No incident diabetes (n = 2590)
Incident diabetes (n = 297)
44 ± 17
47 ± 15
Sex (% women)
Systolic BP (mmHg)
122 ± 17
127 ± 17
Diastolic BP (mmHg)
75 ± 11
78 ± 11
Heart rate (bpm)
68 ± 11
70 ± 11
Body mass index (kg/m2)
30 ± 7
35 ± 7
Waist circumference (cm)
100 ± 16
113 ± 16
GFRMDRD (mL/min/1.73 m2)
187 ± 37
187 ± 39
50 ± 15
44 ± 14
Fasting glucose (mg/dL)
96 ± 13
109 ± 25
Fasting insulin (mIU/mL)
Fat-free mass (kg)
53 ± 12
59 ± 14
Adipose mass (kg)
35 ± 10
40 ± 8
LVDD index (cm/m)
3.09 ± 0.25
3.16 ± 0.29
LV mass index (g/m2.7)
38.0 ± 8.8
42.2 ± 10.3
Relative wall thicknessa
0.32 ± 0.05
0.33 ± 0.04
LAV index (mL/m2)b
11.4 ± 3.0
13.1 ± 3.0
Ejection fraction (%)
63 ± 5
64 ± 5
LV chamber dimension and mass and estimated LA volume were greater in participants developing type 2 diabetes during follow-up, who also exhibited a tendency toward more concentric LV geometry (Table 1). Participants developing type 2 diabetes had a twofold higher prevalence of initial LVH than those remaining with plasma glucose in the non-diabetic range (23 vs. 13%, OR = 2.04 [95% CI = 1.51–2.77], p < 0.0001). Similarly, the prevalence of initial LA dilatation was twofold greater in participants with incident type 2 diabetes (8 vs. 4%, OR = 2.23 [95°CI = 1.39–3.58], p < 0.001). The ratio uAlb/Crea did not exhibit significant difference between the two subpopulations, but participants developing type 2 diabetes were 1.5-fold more likely to have values greater than the 75th percentile of the distribution (32 vs. 23%, OR = 1.55 [1.19–2.01], p < 0.001).
Odds of 4-year incident type 2 diabetes mellitus in relation to specific markers of cardio-renal TOD
High urinary albumin/creatinine
Significant predictors of incident diabetes (by backward logistic regression, including all variables displayed in Fig. 2
95% Conf. interv.
Impaired fasting glucose
Body fat (kg)
Fibrinogen (log10 [mg/dL])
PAI-1 (log10 [mg/dL])
To verify the cofactors that influence the impact of central fat distribution on incident type 2 diabetes, we built a sequential logistic model forcing central fat distribution as the first predictor of incident type 2 diabetes, adjusting for age, sex and relatedness (OR = 3.68 [2.2–5.19], p < 0.0001). In a second step, LVH, impaired fasting glucose and amount of body fat were also forced, and the significant association of central fat distribution with incident type 2 diabetes was attenuated (OR = 1.52 [1.01–2.29], p < 0.05). Finally, inflammatory markers (PAI-1 and fibrinogen) were added in the model with the consequent drop of statistical impact of central fat distribution on probability of incident type 2 diabetes (OR = 1.35 [0.89–2.07], p < 0.155).
In the present study, conducted in an unselected cohort of non-diabetic American Indians, cardiac and renal TOD, generally attributable to type 2 diabetes, preceded the clinical appearance of the disease. This finding confirms, on a population-based scale, findings reported in the observational hypertensive registry of the Campania Salute Network . However, the analysis performed in the SHS cohort at least in part clarifies the possible mechanisms of this apparent reverse-causality association.
Cardio-renal TOD and incident diabetes
Similar to what reported in the Campania Salute Network , in the SHS cohort, cardio-renal TOD was associated with 4-year incident type 2 diabetes, independent of age, sex, family relatedness and, most important, arterial hypertension, but the metabolic phenotype preceding the clinical manifestation of type 2 diabetes could largely explain the temporal association between TOD and incident type 2 diabetes. This metabolic phenotype included insulin resistance, amount of body fat and visceral adiposity. That type 2 diabetes can be predicted by this unfavorable metabolic phenotype is not surprising , but it is of note that LV hypertrophy, LA dilatation and, to some extent, proteinuria precede development of the disease.
We have already shown that these abnormalities were present in the adolescent population of the SHFS with IFG . The sequential logistic model we run in the present analysis largely demonstrate that at the basis of the evidence of TOD preceding detection of type 2 diabetes there are metabolic abnormalities with high potential to have impact on the CV system. This observation is well fitting with cross-sectional and longitudinal analyses demonstrating that substantial CV risk attributable to type 2 diabetes is sustained by the coexisting metabolic abnormalities, often clustered in the metabolic syndrome [28–30]. However, the evidence we provide is specific for cardio-renal TOD, and may not be extrapolated to the vascular bed, a district in which the atherosclerotic evolution is more accelerated in type 2 diabetes than in metabolic syndrome without diabetes . This atherosclerotic evolution is also responsible for specific functional alterations in diabetes, such as increased arterial stiffness .
Influence of arterial hypertension
In multivariable logistic regression, arterial hypertension did not influence the relation between cardio-renal TOD and incident type 2 diabetes, though the prevalence of hypertension in this population was high (40%). This finding is fitting with other observations from the SHS and other epidemiological studies [33–35], demonstrating disagreement between evolution of TOD and blood pressure.
It is also of note that the phenotype at risk of type 2 diabetes emerging from our analysis is not substantially different from that associated with 8-year incident hypertension in SHS participants with NFG and optimal blood pressure at the initial observation . In that study, central fat distribution was a key factor also for incident hypertension, and, interestingly, type 2 diabetes detected after 4 years was independently associated with 2.6-fold greater risk of being hypertensive at the censoring time after 8 years follow-up. Considering all together these findings strongly indicate that both type 2 diabetes and, to some extent, hypertension share a common risk phenotype.
The present analysis also suggests a strong role of central fat distribution-related inflammation in the development of type 2 diabetes . Inflammation was not considered in our analysis on incident hypertension, in which, in fact, central fat distribution was a critical predicting factor , as it was in the present logistic model before entering the inflammatory markers. The link between type 2 diabetes and inflammation has been reported in other studies .
In the present study, we adopted the simplest possible diagnostic criterion for DM, according to ADA recommendations. However, a further in-depth screening, using 2 h OGTT could have revealed more prevalent diabetes, and could even better refine the selection of the study population. However, though it could be appropriate, the current recommendations do not require further diagnostic tests for subjects classified in the range of impaired fasting glucose and our criterion is more adherent to the present clinical practice.
In the SHS, arterial hypertension has been detected using office and not ambulatory BP monitoring. Because the high prevalence of central obesity and IFG, masked hypertension might not be rare in the SHS participants . Thus, we cannot rule out the possibility that the diagnosis of hypertension at the time of initial examination was underestimated.
In our analysis, sex has been used as a covariate, because the lack of adequate power to run sex-specific analyses. However, sex-differences in the relation between both cardio-renal and vascular TOD and incident diabetes might be relevant. The progression of vascular TOD seems to be more accentuated in women than in men [32, 40], and the prevalence of cardiac TOD is higher in women, especially in the presence of central obesity and abnormal body composition [12, 41], both factors predicting incident diabetes.
In this population-based study, we demonstrated that cardio-renal TOD generally attributable to type 2 diabetes precedes the clinical detection of the disease, but is substantially related to the metabolic status preceding diabetes including IFG, body fat accumulation and inflammation.
GdS conceived and designed the project; GdS, RI and CM analyzed data and gave the first interpretation of results; GdS wrote the manuscript, with the contribution of RI, CM and RBD; WW, LGB, FY, MJR, ETL and BH gave critical conceptual contributions during revision of the manuscript. All authors read and approved the final manuscript.
All authors take responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation.
The authors wish to thank the Indian Health Service, the Strong Heart Study Participants, the Participating Tribal Communities and the Strong Heart Study Center Coordinators for their help in the realization of this project.
Views expressed in this paper are those of the authors and do not necessarily reflect those of the Indian Health Service or the Federal Government.
The authors declare that they have no competing interests.
Availability of data and materials
Not applicable. The conclusions of the manuscript are based on relevant data sets available in the manuscript.
Ethics approval and consent to participate, consent for publication
Informed consent was obtained from all patients for being included in the study. All procedures followed were performed in accordance with the ethical standards of the responsible committee on human experimentation and with the 1975 Helsinki Declaration and its later amendments. Center for American Indian Health Research College of Public Health University of Oklahoma Health Sciences Center approved the manuscript.
This work was supported in part by Grants RO1-HL55673, U01-HL54496, U01-HL65521, and M10RR0047-34 from the National Institutes of Health, Bethesda, Maryland.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- de Simone G, Devereux RB, Roman MJ, Chinali M, Barac A, Panza JA, Lee ET, Galloway JM, Howard BV. Does cardiovascular phenotype explain the association between diabetes and incident heart failure? The Strong Heart Study. Nutr Metab Cardiovasc Dis. 2013;23(4):285–91.View ArticlePubMedGoogle Scholar
- Devereux RB, Roman MJ, Paranicas M, O’Grady MJ, Lee ET, Welty TK, Fabsitz RR, Robbins D, Rhoades ER, Howard BV. Impact of diabetes on cardiac structure and function: the strong heart study. Circulation. 2000;101(19):2271–6.View ArticlePubMedGoogle Scholar
- Cioffi G, Faggiano P, Lucci D, Di LA, Mureddu GF, Tarantini L, Verdecchia P, Comaschi M, Giorda CB, Velussi M, et al. Inappropriately high left ventricular mass in patients with type 2 diabetes mellitus and no overt cardiac disease. The DYDA Study. J Hypertens. 2011;29(10):1994–2003.View ArticlePubMedGoogle Scholar
- de Simone G, Devereux RB, Roman MJ, Schlussel Y, Alderman MH, Laragh JH. Echocardiographic left ventricular mass and electrolyte intake predict arterial hypertension. Ann Intern Med. 1991;114(3):202–9.View ArticlePubMedGoogle Scholar
- Izzo R, de Simone G, Devereux RB, Giudice R, De MM, Cimmino CS, Vasta A, De Luca N, Trimarco B. Initial left-ventricular mass predicts probability of uncontrolled blood pressure in arterial hypertension. J Hypertens. 2011;29(4):803–8.View ArticlePubMedGoogle Scholar
- Izzo R, de Simone G, Trimarco V, Gerdts E, Giudice R, Vaccaro O, De Luca N, Trimarco B. Hypertensive target organ damage predicts incident diabetes mellitus. Eur Heart J. 2013;34(44):3419–26.View ArticlePubMedPubMed CentralGoogle Scholar
- Howard BV, Lee ET, Cowan LD, Devereux RB, Galloway JM, Go OT, Howard WJ, Rhoades ER, Robbins DC, Sievers ML, et al. Rising tide of cardiovascular disease in American Indians. The Strong Heart Study. Circulation. 1999;99(18):2389–95.View ArticlePubMedGoogle Scholar
- Lee ET, Fabsitz R, Cowan LD, Le NA, Oopik AJ, Cucchiara AJ, Savage PJ, Howard BV, The Strong Heart Study. A study of cardiovascular disease in American Indians: design and methods. Am J Epidemiol. 1990;136:1141–55.View ArticleGoogle Scholar
- Best LG, North KE, Tracy RP, Lee ET, Howard BV, Palmieri V, MacCluer JW. Genetic determination of acute phase reactant levels: the strong heart study. Hum Hered. 2004;58(2):112–6.View ArticlePubMedGoogle Scholar
- Chinali M, de Simone G, Roman MJ, Lee ET, Best LG, Howard BV, Devereux RB. Impact of obesity on cardiac geometry and function in a population of adolescents: the Strong Heart Study. J Am Coll Cardiol. 2006;47(11):2267–73.View ArticlePubMedGoogle Scholar
- Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C. Definition of metabolic syndrome: report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation. 2004;109(3):433–8.View ArticlePubMedGoogle Scholar
- Ferrara LA, Capaldo B, Mancusi C, Lee ET, Howard BV, Devereux RB, de SG. Cardiometabolic risk in overweight subjects with or without relative fat-free mass deficiency: the Strong Heart Study. Nutr Metab Cardiovasc Dis. 2014;24(3):271–6.View ArticlePubMedGoogle Scholar
- Stolarczyk LM, Heyward VH, Hicks VL, Baumgartner RN. Predictive accuracy of bioelectrical impedance in estimating body composition of Native American women. Am J ClinNutr. 1994;59(5):964–70.Google Scholar
- Association AD. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2007;30(Suppl 1):S42–7.View ArticleGoogle Scholar
- Levey AS, Coresh J, Greene T, Stevens LA, Zhang YL, Hendriksen S, Kusek JW, Van Lente F. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med. 2006;145(4):247–54.View ArticlePubMedGoogle Scholar
- Devereux RB, Roman MJ, de Simone G, O’Grady MJ, Paranicas M, Yeh JL, Fabsitz RR, Howard BV. Relations of left ventricular mass to demographic and hemodynamic variables in American Indians: the Strong Heart Study. Circulation. 1997;96(5):1416–23.View ArticlePubMedGoogle Scholar
- Devereux RB, Roman MJ, Palmieri V, Liu JE, Lee ET, Best LG, Fabsitz RR, Rodeheffer RJ, Howard BV. Prognostic implications of ejection fraction from linear echocardiographic dimensions: the Strong Heart Study. Am Heart J. 2003;146(3):527–34.View ArticlePubMedGoogle Scholar
- Devereux RB, Alonso DR, Lutas EM, Gottlieb GJ, Campo E, Sachs I, Reichek N. Echocardiographic assessment of left ventricular hypertrophy: comparison to necropsy findings. Am J Cardiol. 1986;57(6):450–8.View ArticlePubMedGoogle Scholar
- de Simone G, Kizer JR, Chinali M, Roman MJ, Bella JN, Best LG, Lee ET, Devereux RB. Normalization for body size and population-attributable risk of left ventricular hypertrophy: the Strong Heart Study. Am J Hypertens. 2005;18(2):191–6.View ArticlePubMedGoogle Scholar
- de Simone G, Daniels SR, Kimball TR, Roman MJ, Romano C, Chinali M, Galderisi M, Devereux RB. Evaluation of concentric left ventricular geometry in humans: evidence for age-related systematic underestimation. Hypertension. 2005;45(1):64–8.View ArticlePubMedGoogle Scholar
- Palmieri V, Dahlof B, DeQuattro V, Sharpe N, Bella JN, de Simone G, Paranicas M, Fishman D, Devereux RB. Reliability of echocardiographic assessment of left ventricular structure and function: the PRESERVE study. Prospective randomized study evaluating regression of ventricular enlargement [see comments]. J Am Coll Cardiol. 1999;34(5):1625–32.View ArticlePubMedGoogle Scholar
- Canciello G, de Simone G, Izzo R, Giamundo A, Pacelli F, Mancusi C, Galderisi M, Trimarco B, Losi MA. Validation of left atrial volume estimation by left atrial diameter from the parasternal long-axis view. J Am Soc Echocardiogr. 2017;30(3):262–9.View ArticlePubMedGoogle Scholar
- Kuznetsova T, Haddad F, Tikhonoff V, Kloch-Badelek M, Ryabikov A, Knez J, Malyutina S, Stolarz-Skrzypek K, Thijs L, Schnittger I, et al. Impact and pitfalls of scaling of left ventricular and atrial structure in population-based studies. J Hypertens. 2016;34(6):1186–94.View ArticlePubMedGoogle Scholar
- De Marco M, de Simone G, Roman MJ, Chinali M, Lee ET, Calhoun D, Howard BV, Devereux RB. Cardiac geometry and function in diabetic or prediabetic adolescents and young adults: the Strong Heart Study. Diabetes Care. 2011;34(10):2300–5.View ArticlePubMedPubMed CentralGoogle Scholar
- Barnard J, Meng XL. Applications of multiple imputation in medical studies: from AIDS to NHANES. Stat Methods Med Res. 1999;8(1):17–36.View ArticlePubMedGoogle Scholar
- de Simone G, Izzo R, Losi MA, Stabile E, Rozza F, Canciello G, Mancusi C, Trimarco V, De Luca N, Trimarco B. Depressed myocardial energetic efficiency is associated with increased cardiovascular risk in hypertensive left ventricular hypertrophy. J Hypertens. 2016;34(9):1846–53.View ArticlePubMedGoogle Scholar
- Laaksonen DE, Lakka HM, Niskanen LK, Kaplan GA, Salonen JT, Lakka TA. Metabolic syndrome and development of diabetes mellitus: application and validation of recently suggested definitions of the metabolic syndrome in a prospective cohort study. Am J Epidemiol. 2002;156(11):1070–7.View ArticlePubMedGoogle Scholar
- Alexander CM, Landsman PB, Teutsch SM, Haffner SM. NCEP-defined metabolic syndrome, diabetes, and prevalence of coronary heart disease among NHANES III participants age 50 years and older. Diabetes. 2003;52(5):1210–4.View ArticlePubMedGoogle Scholar
- Howard BV, Best LG, Galloway JM, Howard WJ, Jones K, Lee ET, Ratner RE, Resnick HE, Devereux RB. Coronary heart disease risk equivalence in diabetes depends on concomitant risk factors. Diabetes Care. 2006;29(2):391–7.View ArticlePubMedGoogle Scholar
- de Simone G, Devereux RB, Chinali M, Best LG, Lee ET, Galloway JM, Resnick HE. Prognostic impact of metabolic syndrome by different definitions in a population with high prevalence of obesity and diabetes: the Strong Heart Study. Diabetes Care. 2007;30(7):1851–6.View ArticlePubMedGoogle Scholar
- Gomez-Marcos MA, Recio-Rodriguez JI, Patino-Alonso MC, Agudo-Conde C, Rodriguez-Sanchez E, Maderuelo-Fernandez JA, Gomez-Sanchez L, Gomez-Sanchez M, Garcia-Ortiz L, Group LD. Evolution of target organ damage and haemodynamic parameters over 4 years in patients with increased insulin resistance: the LOD-DIABETES prospective observational study. BMJ Open. 2016;6(6):e010400.View ArticlePubMedPubMed CentralGoogle Scholar
- Gomez-Marcos MA, Recio-Rodriguez JI, Patino-Alonso MC, Agudo-Conde C, Gomez-Sanchez L, Gomez-Sanchez M, Rodriguez-Sanchez E, Maderuelo-Fernandez JA, Garcia-Ortiz L, Group LD. Cardio-ankle vascular index is associated with cardiovascular target organ damage and vascular structure and function in patients with diabetes or metabolic syndrome, LOD-DIABETES study: a case series report. Cardiovasc Diabetol. 2015;14:7.View ArticlePubMedPubMed CentralGoogle Scholar
- de Simone G, Arnett DK, Chinali M, De MM, Rao DC, Kraja AT, Hunt SC, Devereux RB. Partial normalization of components of metabolic syndrome does not influence prevalent echocardiographic abnormalities: the HyperGEN study. Nutr Metab Cardiovasc Dis. 2013;23(1):38–45.View ArticlePubMedGoogle Scholar
- de Simone G, Devereux RB, Izzo R, Girfoglio D, Lee ET, Howard BV, Roman MJ. Lack of reduction of left ventricular mass in treated hypertension: the strong heart study. J Am Heart Assoc. 2013;2(3):e000144.View ArticlePubMedPubMed CentralGoogle Scholar
- Lonnebakken MT, Izzo R, Mancusi C, Gerdts E, Losi MA, Canciello G, Giugliano G, De Luca N, Trimarco B, de Simone G. Left ventricular hypertrophy regression during antihypertensive treatment in an outpatient clinic (the Campania Salute Network). J Am Heart Assoc. 2017;6(3):004.View ArticleGoogle Scholar
- de Simone G, Devereux RB, Chinali M, Roman MJ, Best LG, Welty TK, Lee ET, Howard BV. Risk factors for arterial hypertension in adults with initial optimal blood pressure: the Strong Heart Study. Hypertension. 2006;47(2):162–7.View ArticlePubMedGoogle Scholar
- Bertoni AG, Burke GL, Owusu JA, Carnethon MR, Vaidya D, Barr RG, Jenny NS, Ouyang P, Rotter JI. Inflammation and the incidence of type 2 diabetes: the Multi-Ethnic Study of Atherosclerosis (MESA). Diabetes Care. 2010;33(4):804–10.View ArticlePubMedPubMed CentralGoogle Scholar
- Spranger J, Kroke A, Mohlig M, Hoffmann K, Bergmann MM, Ristow M, Boeing H, Pfeiffer AF. Inflammatory cytokines and the risk to develop type 2 diabetes: results of the prospective population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. Diabetes. 2003;52(3):812–7.View ArticlePubMedGoogle Scholar
- Papadopoulos DP, Makris TK. Masked hypertension definition, impact, outcomes: a critical review. J Clin Hypertens (Greenwich). 2007;9(12):956–63.View ArticleGoogle Scholar
- Gomez-Marcos MA, Recio-Rodriguez JI, Gomez-Sanchez L, Agudo-Conde C, Rodriguez-Sanchez E, Maderuelo-Fernandez J, Gomez-Sanchez M, Garcia-Ortiz L, Group LD. Gender differences in the progression of target organ damage in patients with increased insulin resistance: the LOD-DIABETES study. Cardiovasc Diabetol. 2015;14:132.View ArticlePubMedPubMed CentralGoogle Scholar
- de Simone G, Pasanisi F, Ferrara AL, Roman MJ, Lee ET, Contaldo F, Howard BV, Devereux RB. Relative fat-free mass deficiency and left ventricular adaptation to obesity: the Strong Heart Study. Int J Cardiol. 2013;168(2):729–33.View ArticlePubMedGoogle Scholar