2002
LETTERS TO THE EDITOR
indicating that dysregulation in the growth hormone–IGF-1 axis plays an important role in the pathogenesis of frailty, directly or through other intermediate pathophysiological processes. Clinical replacement trials of growth hormone in healthy older people have had disappointing results,10 leaving the field with lingering unanswered questions about the clinical effect of age-related hormonal changes. Moatassem S. Amer, MD Tamer M. Farid, MD Hoda M. Farid, MD Geriatrics and Gerontology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt Randa A. Mabrouk, MD Clinical Pathology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt Heba G. Saber, MD Geriatrics and Gerontology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt
OCTOBER 2014–VOL. 62, NO. 10
JAGS
PARADOXICAL ASSOCIATION BETWEEN BODY MASS INDEX, RENAL PROGRESSION, AND CARDIOVASCULAR DISEASE IN ELDERLY ADULTS WITH TYPE 2 DIABETES MELLITUS To the Editor: Obesity is consistently associated with greater risk of diabetes mellitus, hypertension, chronic kidney disease (CKD), and cardiovascular disease (CVD) in the general population,1–3 but several studies have suggested an inverse relationship between excess weight and adverse outcomes in individuals with CKD.1,4 Consequently, the following question is raised: Does the interaction between obesity, renal progression, and CVD remain the same, or is it reversed in elderly adults with type 2 diabetes mellitus (T2DM), for whom the renal and cardiovascular risks are already very high? The aim of this study was to determine the association between body mass index (BMI), estimated glomerular filtration rate (eGFR), and occurrence of CVD in a prospective cohort of elderly adults with T2DM in a developing country.
METHODS ACKNOWLEDGMENTS Conflict of Interest: The editor in chief has reviewed the conflict of interest checklist provided by the authors and has determined that the authors have no financial or any other kind of personal conflicts with this paper. Author Contributions: Amer M.S.: study design, interpretation of data, revising the manuscript. Farid T.M., Farid H.M.: study design, interpretation of data. Mabrouk R.A.: laboratory assessment. Saber H.G.: study design, data collection, interpretation of data, writing the manuscript. Sponsor’s Role: No sponsor.
REFERENCES 1. Song X, Mitnitski A, Rockwood K. Prevalence and 10-year outcomes of frailty in older adults in relation to deficit accumulation. J Am Geriatr Soc 2010;58:681–687. 2. Graham JE, Snih SA, Berges IM et al. Frailty and 10-year mortality in community-living Mexican American older adults. Gerontology 2009;55:644–651. 3. Klein BE, Klein R, Knudtson MD et al. Frailty, morbidity and survival. Arch Gerontol Geriatr 2005;41:141–149. 4. Maggio M, Guralnik JM, Longo DL et al. Interleukin-6 in aging and chronic disease: A magnificent pathway. J Gerontol A Biol Sci Med Sci 2006;61A:575–584. 5. Cappola AR, Xue QL, Ferrucci L et al. Insulin-like growth factor I and interleukin-6 contribute synergistically to disability and mortality in older women. J Clin Endocrinol Metab 2003;88:2019–2025. 6. Leng SX, Cappola AR, Andersen RE et al. Serum levels of insulin-like growth factor-I (IGF-I) and dehydroepiandrosterone sulfate (DHEA-S), and their relationships with serum interleukin-6, in the geriatric syndrome of frailty. Aging Clin Exp Res 2004;16:153–157. 7. Lee SJ, Lindquist K, Segal MR et al. Development and validation of a prognostic index for 4-year mortality in older adults. JAMA 2006;295: 801–808. 8. Avila-Funes JA, Helmer C, Amieva H et al. Frailty among communitydwelling elderly people in France: The Three-City Study. J Gerontol A Biol Sci Med Sci 2008;63A:1089–1096. 9. Cappola AR, Xue QL, Fried LP. Multiple hormonal deficiencies in anabolic hormones are found in frail older women: The Women’s Health and Aging studies. J Gerontol A Biol Sci Med Sci 2009;64A:243–248. 10. Liu H, Bravata DM, Olkin I et al. Systematic review: The safety and efficacy of growth hormone in the healthy elderly. Ann Intern Med 2007;146:104–115.
This prospective study was begun in September 2007 and was conducted at the Reference Center for Chronic Diseases in Oujda, Morocco. The ethics committee of Morocco’s Mohammed V University in Rabat approved the study protocol. Oral informed consent was required from all participants. Inclusion criteria were aged 65 and older with confirmed T2DM. Exclusion criteria were having only one single kidney, a pathology other than diabetes mellitus, hypertension capable of altering renal function, end-stage renal disease at the time of the enrollment, and follow-up of less than 36 months. Rapid progression was defined as sustained decline in eGFR of more than 5 mL/min per 1.73 m2 per year. The rate of eGFR decline for each individuals was determined as (last eGFR–baseline eGFR)/follow-up period in years.
Statistical Analysis Data were analyzed using the SPSS version 13.0 (SPSS, Inc., Chicago, IL). Comparison of quantitative variables between four groups was performed using analysis of variance (ANOVA) if the variable was symmetrically distributed or the Kruskal–Wallis test if the variable was asymmetrically distributed. Comparison of qualitative variables between four groups was performed using the chi-square test. To explore the possibility that the risk function was nonlinear, the relationship between BMI and renal progression was examined using restricted cubic splines.5 Nonlinearity was tested using the likelihood ratio, comparing the model with only the linear term to the model with the linear and the cubic spline terms. A logistic regression model was fitted with restricted cubic splines for BMI as continuous variables.6 Three knot positions were specified at the 10th, 50th, and 90th percentiles of past BMI, that is, at BMI values of 22.5, 27.8, and 34.2 kg/m2, respectively.7 The reference BMI was 22.5 kg/m2.
JAGS
OCTOBER 2014–VOL. 62, NO. 10
LETTERS TO THE EDITOR
2003
Table 1. Clinical and Biological Characteristics According to Body Mass Index in Elderly Adults with Type 2 Diabetes Mellitus at the Time of Enrollment and at the End of Follow-Up Body Mass Index (kg/m²)
Characteristic
Total, N = 224
At the time of the enrollment Female, n (%) 397 (62.3) Age, mean SD 71 5.5 Duration of diabetes mellitus, years, 8 (3–13) median (IQR) 28.3 4.6 Body mass index, kg/m2, mean SD Family history of diabetes, n (%) 115 (51.3) History of smoking, n (%) 18 (8.2) History of hypertension, n (%) 144 (64.3) History of vascular comorbidities, n (%) 45 (20.1) Ischemic heart disease 34 (15.2) Peripheral vascular disease 11 (4.9) Diabetic retinopathy, n (%) 94 (42) Diabetic neuropathy, n (%) 105 (46.9) Diabetes treatment, n (%) Insulin 138 (6.6) Diabetes pills 159 (71) Hypertension, n (%) 95 (42.4) Systolic blood pressure, mmHg, 145 19 mean SD Diastolic blood pressure, mmHg, 78 10 mean SD Estimated glomerular filtration rate, mL/min per 1.73m2 Median (IQR) Cockcroft–Gault 59 (40–76) Modification of diet in renal disease 78 (57–95) ≥60, n (%) 152 (67.9) 30–59, n (%) 55 (24.6) 15–29, n (%) 17 (7.6) AER, mg/day, median (IQR) 70 (35–219) AER stage (mg/day), n (%) Normo-albuminuria (300) 44 (19.6) Total cholesterol, g/L, mean SD 1.96 0.40 High-density lipoprotein cholesterol, 0.42 0.06 g/L, mean SD Low-density lipoprotein cholesterol, 1.23 0.36 g/L, mean SD Triglycerides, g/L, mean SD 1.36 0.65 Glycosylated hemoglobin, %, 8.4 1.7 mean SD At the end of the follow-up Mean length of follow-up, months, 37 9 meanSD Statin use, n (%) 86 (38.4) Angiotensin-converting enzyme 204 (91.1) inhibitor or angiotensin receptor blocker use, n (%) Using >2 antihypertensive 96 (42.9) drugs, n (%) Rapid progression, n (%) 40 (17.9) Cardiovascular events, n (%) 55 (24.5) Ischemic heart disease 37 (16.5) Peripheral vascular disease 18 (8)
LETTERS TO THE EDITOR
indicating that dysregulation in the growth hormone–IGF-1 axis plays an important role in the pathogenesis of frailty, directly or through other intermediate pathophysiological processes. Clinical replacement trials of growth hormone in healthy older people have had disappointing results,10 leaving the field with lingering unanswered questions about the clinical effect of age-related hormonal changes. Moatassem S. Amer, MD Tamer M. Farid, MD Hoda M. Farid, MD Geriatrics and Gerontology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt Randa A. Mabrouk, MD Clinical Pathology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt Heba G. Saber, MD Geriatrics and Gerontology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt
OCTOBER 2014–VOL. 62, NO. 10
JAGS
PARADOXICAL ASSOCIATION BETWEEN BODY MASS INDEX, RENAL PROGRESSION, AND CARDIOVASCULAR DISEASE IN ELDERLY ADULTS WITH TYPE 2 DIABETES MELLITUS To the Editor: Obesity is consistently associated with greater risk of diabetes mellitus, hypertension, chronic kidney disease (CKD), and cardiovascular disease (CVD) in the general population,1–3 but several studies have suggested an inverse relationship between excess weight and adverse outcomes in individuals with CKD.1,4 Consequently, the following question is raised: Does the interaction between obesity, renal progression, and CVD remain the same, or is it reversed in elderly adults with type 2 diabetes mellitus (T2DM), for whom the renal and cardiovascular risks are already very high? The aim of this study was to determine the association between body mass index (BMI), estimated glomerular filtration rate (eGFR), and occurrence of CVD in a prospective cohort of elderly adults with T2DM in a developing country.
METHODS ACKNOWLEDGMENTS Conflict of Interest: The editor in chief has reviewed the conflict of interest checklist provided by the authors and has determined that the authors have no financial or any other kind of personal conflicts with this paper. Author Contributions: Amer M.S.: study design, interpretation of data, revising the manuscript. Farid T.M., Farid H.M.: study design, interpretation of data. Mabrouk R.A.: laboratory assessment. Saber H.G.: study design, data collection, interpretation of data, writing the manuscript. Sponsor’s Role: No sponsor.
REFERENCES 1. Song X, Mitnitski A, Rockwood K. Prevalence and 10-year outcomes of frailty in older adults in relation to deficit accumulation. J Am Geriatr Soc 2010;58:681–687. 2. Graham JE, Snih SA, Berges IM et al. Frailty and 10-year mortality in community-living Mexican American older adults. Gerontology 2009;55:644–651. 3. Klein BE, Klein R, Knudtson MD et al. Frailty, morbidity and survival. Arch Gerontol Geriatr 2005;41:141–149. 4. Maggio M, Guralnik JM, Longo DL et al. Interleukin-6 in aging and chronic disease: A magnificent pathway. J Gerontol A Biol Sci Med Sci 2006;61A:575–584. 5. Cappola AR, Xue QL, Ferrucci L et al. Insulin-like growth factor I and interleukin-6 contribute synergistically to disability and mortality in older women. J Clin Endocrinol Metab 2003;88:2019–2025. 6. Leng SX, Cappola AR, Andersen RE et al. Serum levels of insulin-like growth factor-I (IGF-I) and dehydroepiandrosterone sulfate (DHEA-S), and their relationships with serum interleukin-6, in the geriatric syndrome of frailty. Aging Clin Exp Res 2004;16:153–157. 7. Lee SJ, Lindquist K, Segal MR et al. Development and validation of a prognostic index for 4-year mortality in older adults. JAMA 2006;295: 801–808. 8. Avila-Funes JA, Helmer C, Amieva H et al. Frailty among communitydwelling elderly people in France: The Three-City Study. J Gerontol A Biol Sci Med Sci 2008;63A:1089–1096. 9. Cappola AR, Xue QL, Fried LP. Multiple hormonal deficiencies in anabolic hormones are found in frail older women: The Women’s Health and Aging studies. J Gerontol A Biol Sci Med Sci 2009;64A:243–248. 10. Liu H, Bravata DM, Olkin I et al. Systematic review: The safety and efficacy of growth hormone in the healthy elderly. Ann Intern Med 2007;146:104–115.
This prospective study was begun in September 2007 and was conducted at the Reference Center for Chronic Diseases in Oujda, Morocco. The ethics committee of Morocco’s Mohammed V University in Rabat approved the study protocol. Oral informed consent was required from all participants. Inclusion criteria were aged 65 and older with confirmed T2DM. Exclusion criteria were having only one single kidney, a pathology other than diabetes mellitus, hypertension capable of altering renal function, end-stage renal disease at the time of the enrollment, and follow-up of less than 36 months. Rapid progression was defined as sustained decline in eGFR of more than 5 mL/min per 1.73 m2 per year. The rate of eGFR decline for each individuals was determined as (last eGFR–baseline eGFR)/follow-up period in years.
Statistical Analysis Data were analyzed using the SPSS version 13.0 (SPSS, Inc., Chicago, IL). Comparison of quantitative variables between four groups was performed using analysis of variance (ANOVA) if the variable was symmetrically distributed or the Kruskal–Wallis test if the variable was asymmetrically distributed. Comparison of qualitative variables between four groups was performed using the chi-square test. To explore the possibility that the risk function was nonlinear, the relationship between BMI and renal progression was examined using restricted cubic splines.5 Nonlinearity was tested using the likelihood ratio, comparing the model with only the linear term to the model with the linear and the cubic spline terms. A logistic regression model was fitted with restricted cubic splines for BMI as continuous variables.6 Three knot positions were specified at the 10th, 50th, and 90th percentiles of past BMI, that is, at BMI values of 22.5, 27.8, and 34.2 kg/m2, respectively.7 The reference BMI was 22.5 kg/m2.
JAGS
OCTOBER 2014–VOL. 62, NO. 10
LETTERS TO THE EDITOR
2003
Table 1. Clinical and Biological Characteristics According to Body Mass Index in Elderly Adults with Type 2 Diabetes Mellitus at the Time of Enrollment and at the End of Follow-Up Body Mass Index (kg/m²)
Characteristic
Total, N = 224
At the time of the enrollment Female, n (%) 397 (62.3) Age, mean SD 71 5.5 Duration of diabetes mellitus, years, 8 (3–13) median (IQR) 28.3 4.6 Body mass index, kg/m2, mean SD Family history of diabetes, n (%) 115 (51.3) History of smoking, n (%) 18 (8.2) History of hypertension, n (%) 144 (64.3) History of vascular comorbidities, n (%) 45 (20.1) Ischemic heart disease 34 (15.2) Peripheral vascular disease 11 (4.9) Diabetic retinopathy, n (%) 94 (42) Diabetic neuropathy, n (%) 105 (46.9) Diabetes treatment, n (%) Insulin 138 (6.6) Diabetes pills 159 (71) Hypertension, n (%) 95 (42.4) Systolic blood pressure, mmHg, 145 19 mean SD Diastolic blood pressure, mmHg, 78 10 mean SD Estimated glomerular filtration rate, mL/min per 1.73m2 Median (IQR) Cockcroft–Gault 59 (40–76) Modification of diet in renal disease 78 (57–95) ≥60, n (%) 152 (67.9) 30–59, n (%) 55 (24.6) 15–29, n (%) 17 (7.6) AER, mg/day, median (IQR) 70 (35–219) AER stage (mg/day), n (%) Normo-albuminuria (300) 44 (19.6) Total cholesterol, g/L, mean SD 1.96 0.40 High-density lipoprotein cholesterol, 0.42 0.06 g/L, mean SD Low-density lipoprotein cholesterol, 1.23 0.36 g/L, mean SD Triglycerides, g/L, mean SD 1.36 0.65 Glycosylated hemoglobin, %, 8.4 1.7 mean SD At the end of the follow-up Mean length of follow-up, months, 37 9 meanSD Statin use, n (%) 86 (38.4) Angiotensin-converting enzyme 204 (91.1) inhibitor or angiotensin receptor blocker use, n (%) Using >2 antihypertensive 96 (42.9) drugs, n (%) Rapid progression, n (%) 40 (17.9) Cardiovascular events, n (%) 55 (24.5) Ischemic heart disease 37 (16.5) Peripheral vascular disease 18 (8)
