|Year : 2022 | Volume
| Issue : 3 | Page : 139-144
An observational study of risk association of diabetes mellitus and hypertension in the first-degree relatives of patients with diabetes mellitus
Divya Rani1, Pradyumna Kumar Singh2
1 Department of Medicine, Holy Family Hospital, Delhi, India
2 Department of Medicine, Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana, India
|Date of Submission||07-Feb-2022|
|Date of Decision||27-Mar-2022|
|Date of Acceptance||11-Apr-2022|
|Date of Web Publication||21-Sep-2022|
212 Ashirwad Enclave, L.P. Extension, Delhi - 110 092
Source of Support: None, Conflict of Interest: None
Background: Occurence of diabetes and hypertension is affected by the genetic modulation and environmental factors. Thus it becomes important to determine associated factors governing them among the relatives. Aims and Objectives: The objectives of this study were to determine the prevalence of diabetes mellitus (DM) and hypertension (HTN) and associated risk factors in the first-degree relatives (FDRs) of the patients with type 2 DM (T2DM). Materials and Methods: The study design was cross-sectional for a period of 18 months from September 2017 to March 2019 wherein 200 people who were FDRs of T2DM patients, visiting Holy Family Hospital, New Delhi, were enrolled. The demographic details, anthropometric measurements, blood pressure and HbA1c levels were assessed, based on which the FDRs were classified into pre-diabetes, diabetes and hypertensive. The odds ratio was calculated for risk association to predict the occurrence of DM and HTN. Results: The age of the study population ranged from 30 to 50.25 years, with a median age of 38 years. There were 116 (58%) males and 84 (42%) females. The median body mass index (BMI) was 24.5, with 49.5% having normal BMI, 43% being pre-obese and 7.5% obese. As per the glycaemic parameters, 80 (40%) had normal glucose tolerance, 50 (25%) were pre-diabetic and 70 (35%) had diabetes. Amongst the 200 FDRs, HTN was prevalent in 95 (47.5%) cases. Higher age was found to be a significant risk factor for DM, with a higher odds of 1.056 (P = 0.021), while higher age and female gender carried a significantly higher odds of occurrence of HTN in FDRs, with an odds ratio of 1.049 and 2.178. Conclusion: DM and HTN are prevalent in FDRs of T2DM patients. Higher age is a significant risk factor for both DM and HTN, necessitating a regular screening of FDRs for an early interception to prevent these diseases.
Keywords: Diabetes mellitus, first-degree relatives, hypertension, risk factors
|How to cite this article:|
Rani D, Singh PK. An observational study of risk association of diabetes mellitus and hypertension in the first-degree relatives of patients with diabetes mellitus. Hamdan Med J 2022;15:139-44
|How to cite this URL:|
Rani D, Singh PK. An observational study of risk association of diabetes mellitus and hypertension in the first-degree relatives of patients with diabetes mellitus. Hamdan Med J [serial online] 2022 [cited 2022 Oct 7];15:139-44. Available from: http://www.hamdanjournal.org/text.asp?2022/15/3/139/356436
| Introduction|| |
Diabetes mellitus (DM) marks one of those diseases, which shows high prevalence both in developing and developed countries. The global prevalence of diabetes as estimated by the International Diabetes Federation (2019) was 9.3% which amounted to around 463 million population which is expected to rise by 25% in the next 10 years up to 2030.
In the current times of the pandemic, DM has shown a significant association with morbidity and mortality arising out of infection with COVID-19. Considering the significant nature of diabetes, medical literature does not fall back on introducing screening tests for early diagnosis of diabetes which includes routine blood glucose examinations in the fasting and postprandial state, glycosylated haemoglobin (HbA1c), insulin fasting and postprandial and HOMA-IR index.
Amongst these tests, HbA1c is an important long-term marker for glycaemic control. Recently, various guidelines have proposed a cut-off of HbA1c for diagnosing a patient with no diabetes, pre-diabetes and diabetes. Although, as a single test, HbA1c carries a low sensitivity of 65%, overall, it shows a good specificity of 94% in diagnosing diabetes.
When we consider the risk factors of diabetes, research shows that genetic mutations and family history of diabetes are relevant predictors of diabetes development in first-degree relatives (FDRs)., Besides, Janghorbani et al. showed that hypertension (HTN) coexists with diabetes resulting in cardiovascular morbidities.
Sparse studies have focused on the diabetes prevalence in FDRs of confirmed diabetic populations. This remains of significant concern in a country like ours since the awareness levels of the general population remain low in regard to association of family history with diabetes.
This not only brings down the early detection of diabetes in the population which are more prone to diabetes, but it also enhances the development of complications in such population following the occurrence of diabetes such as HTN, dyslipidaemia and metabolic syndrome.,,
In view of this, we conducted the present study with an objective to assess DM, HTN prevalence and associated risk factors amongst FDRs of DM patients.
| Methods|| |
The study design was cross-sectional for a period of 18 months from September 2017 to March 2019 wherein 200 people who were FDRs of DM patients, visiting Holy Family Hospital, New Delhi, were enrolled.
- FDR of a person, who is documented to be a patient of type 2 DM (T2DM)
- Age >18 years.
- Persons not willing to participate in the study
- Pregnant patients
- Persons suffering from anaemia, haemoglobinopathies, chronic renal disease, pancreatitis and history of chronic alcohol intake
- Persons already diagnosed with DM or HTN.
Sample size calculation
The sample size selected for the present study was based on previous studies where the prevalence of undiagnosed diabetes ranged from 8.5% to 11.57%.,, Considering them for references with a 5% chance of error and significant level, 158 patients were required to proceed with the study. Further considering the dropouts, a sample of 200 was enrolled.
For all the enrolled FDRs of T2DM patients, the details pertaining to the age, gender, body mass index (BMI) as per Quetelet's formula, blood pressure (BP) and HbA1c levels were recorded.
Standards and criteria
BMI was classified as per the WHO classification with three categories of normal BMI from 18.5 to 24.9, pre-obese BMI from 25.0 to 29.9 and obese BMI which was ≥30 kg/m2.
The recordings of the BP were taken from the dominant arm with the individual seated after resting for 5 min, with the use of a standard adult Heine aneroid sphygmomanometer. Two readings were taken 5 min apart, and an average of systolic and diastolic BP was calculated and reported. People were classified into three categories: (1) normotensives with systolic <120 mmHg and diastolic less than 80 mmHg, (2) elevated with systolic ranging from 120 to 129 mmHg and diastolic <80 mmHg and hypertensives with systolic more than or equal to 130 mmHg and diastolic more than or equal to 80 mmHg, according to new guidelines of ACC/AHA.
For HbA1c testing, a 2-ml venous blood sample was collected. HbA1c was measured within 2 h using high-performance liquid chromatography. Based on HbA1c values, the patients were labelled as either pre-diabetic with HbA1c varying between 5.7 and 6.4 g% or diabetic with HbA1c more than or equal to 6.5 g%.
Physical examination was also done wherein acanthosis nigricans was identified as symmetrically distributed hyperpigmented and velvety textured plaques found at any body part. Skin tags were identified as small soft and pedunculated protrusions of brown or skin coloured with a diameter varying between 1 and 10 mm. The diagnostic criteria for polycystic ovarian syndrome (PCOS) in women included two of the following three criteria (Rotterdam's criteria): chronic anovulation, hyperandrogenism (clinical/biologic) and polycystic ovaries.
The final data were compiled and represented in the form of a number (n) and percentage (%) for categorical variables and the form of the mean (with standard deviation) or median (with the third quartile range: 25th to 75th) for quantitative variables. Normality was assessed by Kolmogorov–Smirnov test; and non-parametric tests were used if the data were not normally distributed.
The association of age was done by Kruskal–Wallis test (>2 groups) and Mann–Whitney test (two groups). Mann Whitney test, Fisher's exact test and Chi-square test were used for determining the association of variables with diabetes. The association of BMI and PCOS with normal glucose tolerance (NGT), pre-diabetes and diabetes was analysed by Fisher's exact test and association of gender, HTN, acanthosis nigricans, skin tags with NGT, pre-diabetes and diabetes and association of gender, HTN, acanthosis nigricans, skin tags, BMI, PCOS with diabetes and association of gender, acanthosis nigricans, skin tags, BMI, PCOS with HTN was analysed by Chi-square test. Multivariate logistic regression derived the odds ratio of the risk factors for the occurrence of DM and HTN.
The values were considered to be significantly associated if the P < 0.05. The complete statistical analysis was done using the 'Statistical Package for Social Sciences (SPSS) software, IBM manufacturer, Chicago, Illinois, USA, ver. 21.0'.
| Results|| |
Demographics of first-degree relatives
The age of the study population ranged from 30 to 50.25 years, with a median age of 38 years. There were 58% (n = 116) of males and 42% (n = 84) of females. The median BMI was 24.5, with 49.5% having normal BMI, 43% being pre-obese and 7.5% obese. As per the glycaemic parameters, 80 (40%) had NGT, 50 (25%) were pre-diabetic and 70 (35%) had diabetes. Amongst the 200 FDRs, HTN was prevalent in 95 (47.5%) cases. Other findings included skin tags in 27 (13.5%) cases, PCOS in 18 (9%) cases and acanthosis nigricans in 30 (15%) cases [Table 1].
Diabetes (n = 70) versus non-diabetes (n = 130)
Compared to population with non-diabetes (including pre-diabetes), diabetics FDRs had significantly higher age (45 vs. 34, P < 0.0001), comparable gender distribution, significantly higher BMI (P = 0.007) with more pre-obese (51.43% vs. 38.46%) and obese (12.86% vs. 4.62%), significantly more cases of HTN (60% vs. 40.77%, P = 0.009), significantly more cases of skin tags (20% vs. 10%, P = 0.048), PCOS (37.5% vs. 11.76%, P = 0.006) and acanthosis nigricans (28.57% vs. 7.69%, P < 0.0001), respectively [Table 2].
Higher age was found to be a significant risk factor for DM amongst FDRs, with a higher odds of 1.056 (P = 0.021), as shown in [Table 3].
Hypertensive (n = 95) versus non-hypertensive (n = 105)
Compared to population with no HTN, hypertensives FDRs had significantly higher age (43 vs. 32, P < 0.0001), higher number of females (50.53% vs. 34.29%, P = 0.02), comparable BMI (P = 0.097), skin tags (13.68% vs. 13.33%, P = 0.942), PCOS (25% vs. 17.14%, P = 0.391) and acanthosis nigricans (17.89% vs. 12.38%, P = 0.275), respectively [Table 4].
Higher age and female gender carried a significantly higher odds of occurrence of HTN in FDRs, with an odds ratio of 1.049 (P < 0.0001) and 2.178 (P = 0.011), respectively, as shown in [Table 5].
| Discussion|| |
We showed that HTN and DM are significantly associated with FDRs in the diabetic.
Our data also are in resonance with the observation done earlier who showed that 2-h post-load glucose concentration, FPG and IGT were associated with incident HTN., Miyai et al. in a Japanese study reported that hyperglycaemic patients had a considerably higher mean arterial pressure z-score than those without metabolic syndrome components.
There is not much clarity on the mechanisms behind the increase in HTN risk in people who have hyperglycaemia. The common factors behind the association between type 2 diabetes mellitus (T2D), HTN and obesity are hyperinsulinaemia and insulin resistance. With time, glucose levels increase, and insulin secretion decreases in patients with impaired glucose metabolism. In non-diabetic people, insulin is described to have a small BP-lowering effect. This finding suggests that if the activation of the insulin pathway reduces because of a decrease in the insulin secretion capacity, especially when insulin resistance is present, it can help HTN development through endothelial dysfunction.
Over time because of possible frequent rises in postprandial glucose levels, HTN development might occur through a subtle defect in the beta-cell function. BP might also increase because of glycaemic variability through 'elevated oxidative stress and chronic induction of inflammation'. Both the BP variability and glycaemic fluctuations are linked with the 'oxidative stress', which points towards the possibility of an alternate process for the clarification of the increase in the incidence of HTN in relation to beta-cell function defect. Degeneration of the wall of arteries might also occur due to hyperglycaemia through 'activation of protein kinase C, production of reactive oxygen species and deposition of the advanced glycation end product'. Chronically high blood glucose also causes the arterial walls to lose their elasticity. HTN occurs in response to a reduction in elasticity due to an increase in peripheral vascular resistance.,
Further, we also observed that obesity is an intricate link between diabetes and HTN, with higher BMI showing a significant association with diabetes.
For a long time, the relationship between obesity and T2DM has been very well known where both have been shown as directly proportional to each other. Furthermore, in obese people, a higher incidence is found of diabetes and impaired fasting blood glucose levels indicating a strong link between the development of DM in obese people, who are FDRs of people who have T2DM.
Ali et al. stated a strong link between high fasting glucose and higher BMI. It was seen in this study that values of BMI were found to be higher in people who have diabetes.
In one of the studies by Muktabhant et al., BMI showed a significant association with the occurrence of diabetes after adjustment of various confounders, with an odds ratio of 2.01 (P = 0.007). However, in our study, after adjustments of confounders, BMI was not found to be a significant risk factor for DM/HTN. Related risk factors with type 2 diabetes as per a recent review article are family history of DM and higher BMI.
With regards to obesity, studies have deciphered different biochemical substances known as adipokines which include 'omentin-1, adiponectin, retinol-binding protein-4 and visfatin'. These substances connect neuroendocrine function, energy homeostasis, immunity, T2DM, atherosclerosis and IR. Considering these facts and certain evidences to support that if weight is managed well, then progression from pre-diabetes to T2DM can be slowed; such patients should undertake lifestyle modifications such as exercise, dietary changes, cessation of smoking and weight reduction.
As per studies, a pre-diabetic adult population should be given lifestyle modification as a treatment option to better manage their blood glucose and decrease their chances of developing type 2 diabetes. Doctors can do better healthcare counselling people at increased risk so that the onset of type 2 diabetes could be delayed or prevented.
Amongst the various risk factors, we found that higher age significantly increased the odds of DM (OR = 1.056) and HTN (OR = 1.049). Even in Muktabhant et al., age carried a significantly higher odds of diabetes, with an odds ratio of 2.26 (P = 0.001). Even in another study, amongst the middle-aged and elderly, the chances of HTN were increased by odds of 1.4–1.55 (P < 0.05) with increasing severity of blood sugar levels and insulin resistance. This may be ascribed to the association of increasing age with low arterial elasticity and continuous metabolic alterations.,
We also found that the female gender in FDRs carried a higher odds of HTN (OR = 2.178) but not DM. Observed gender differences in HTN might be because of biological factors such as different hormones, genetic chromosomal differences and behavioural factors in terms of lifestyle, smoking habits and mental health.
Limitations of the study
The present study suffers from the limitation of a cross-sectional study design where no follow-up of the FDRs could be done. Second, the diet, smoking, stress and salt intake in diet were not assessed amongst the FDRs since they may have a significant impact on the risk of development of DM. Third, the duration of diabetic patients was not noted. Finally, plasma oxidative stress or inflammatory markers were not analysed since they are costly phenomena in India.
| Conclusion|| |
DM and HTN are prevalent in FDRs of patients with T2DM. Obesity holds an intermediary association in the occurrence of DM. Independently, higher age was found to be a significant risk factor for DM and age and female gender were risk factors for HTN, necessitating a regular screening of FDRs for an early interception to prevent these diseases.
The present research is in complete compliance with the guidelines laid by the EQUATOR Network. A formal clearance was obtained from the Ethical Committee of the Holy family hospital, New Delhi - 110025 (IEC registration number: 111-20118-171-212760, dated July 20, 2017).
Duly informed written consent was taken from the T2DM patients and their FDRs.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, et al.
Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th
edition. Diabetes Res Clin Pract 2019;157:107843.
Gupta P, Gupta M, KAtoch N, Garg K, Garg B. A systematic review and meta-analysis of diabetes associated mortality in patients with COVID-19. Int J Endocrinol Metab 2021;19:e113220.
Pippitt K, Li M, Gurgle HE. Diabetes mellitus: Screening and diagnosis. Am Fam Physician 2016;93:103-9.
Osei K, Rhinesmith S, Gaillard T, Schuster D. Is glycosylated hemoglobin A1c a surrogate for metabolic syndrome in nondiabetic, first-degree relatives of African-American patients with type 2 diabetes? J Clin Endocrinol Metab 2003;88:4596-601.
Hu X, Pan X, Ma X, Luo Y, Xu Y, Xiong Q, et al.
Contribution of a first-degree family history of diabetes to increased serum adipocyte fatty acid binding protein levels independent of body fat content and distribution. Int J Obes (Lond) 2016;40:1649-54.
Janghorbani M, Bonnet F, Amini M. Glucose and the risk of hypertension in first-degree relatives of patients with type 2 diabetes. Hypertens Res 2015;38:349-54.
Xu Y, Shen Y, Ma X, Gu C, Wang Y, Bao Y. First-degree family history of diabetes and its relationship with serum osteocalcin levels independent of liver fat content in a non-diabetic Chinese cohort. BMC Public Health 2019;19:1628.
Sathiyapriya V, Bobby Z, Agrawal A, Selvaraj N. Protein glycation, insulin sensitivity and pancreatic beta cell function in high-risk, non-diabetic, first degree relatives of patients with type 2 diabetes. Indian J Physiol Pharmacol 2009;53:163-8.
Eknoyan G. Adolphe Quetelet (1796-1874)-the average man and indices of obesity. Nephrol Dial Transplant 2008;23:47-51.
Whelton PK, Carey RM, Aronow WS, Casey DE Jr., Collins KJ, Dennison Himmelfarb C, et al.
2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: Executive summary: A report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension 2018;71:1269-324.
Rotterdam ESHRE/ASRM-Sponsored PCOS Consensus Workshop Group. Revised 2003 consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome. Fertil Steril 2004;81:19-25.
Goel K, Rajput R, Kharb S. Association of vitamin D levels with blood pressure changes and mean arterial pressure in prediabetics. Biomed Biotechnol Res J 2019;3:253-7. [Full text]
Nair R, Sud R, Swamy A, Patra V. Unmasking previously unrecognized peripheral arterial disease in patients with coronary artery disease using continuous wave Doppler using continuous wave Doppler imaging: Does the presence of peripheral arterial disease influence the clinicopathological profile of coronary artery disease? An Indian study. Biomed Biotechnol Rec 2021;5:50-4.
Miyai N, Shiozaki M, Yabu M, Utsumi M, Morioka I, Miyashita K, et al.
Increased mean arterial pressure response to dynamic exercise in normotensive subjects with multiple metabolic risk factors. Hypertens Res 2013;36:534-9.
Abdul-Hadi MH, Naji MT, Shams HA, Sami OM, Al-Harchan NA, Al-Kuraishy HM, et al
. Oxidative stress injury and glucolipotoxicity in type 2 diabetes mellitus: The potential role of metformin and sitagliptin. Biomed Biotechnol Res J 2020;4:166-72. [Full text]
Ali A, Taj A, Ahmed MU, Tabrez E. Frequency of impaired fasting glucose in first degree relatives of Type-II diabetic patients and its association with Body Mass Index. Pak J Med Sci 2020;36:407-11.
Muktabhant B, Sanchaisuriya P, Trakulwong M, Mingchai R, Schelp FP. A first-degree relative with diabetes mellitus is an important risk factor for rural Thai villagers to develop type 2 diabetes mellitus. Asia Pac J Public Health 2015;27:385-93.
Kerrison G, Gillis RB, Jiwani SI, Alzahrani Q, Kok S, Harding SE, et al.
The effectiveness of lifestyle adaptation for the prevention of prediabetes in adults: A systematic review. J Diabetes Res 2017;2017:8493145.
Sasaki N, Ozono R, Maeda R, Higashi Y. Risk of hypertension in middle-aged and elderly participants with newly diagnosed type 2 diabetes and prediabetes. BMJ Open Diabetes Res Care 2020;8:e001500.
Olaniyan MF, Ojediran TB. Inflammatory response in relationship with the degree of hyperglycemia and expression of viral immune products in diabetes mellitus patients. Biomed Biotechnol Res J 2021;5:398-404. [Full text]
Chia CW, Egan JM, Ferrucci L. Age-related changes in glucose metabolism, hyperglycemia, and cardiovascular risk. Circ Res 2018;123:886-904.
Everett B, Zajacova A. Gender differences in hypertension and hypertension awareness among young adults. Biodemography Soc Biol 2015;61:1-17.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]