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Year : 2022  |  Volume : 21  |  Issue : 3  |  Page : 255-261  

The ambulatory blood pressure monitoring among obese and nonobese diabetes mellitus patients

Department of Internal Medicine, JSS AHER, Mysore, Karnataka, India

Date of Submission27-Mar-2021
Date of Decision22-Jul-2021
Date of Acceptance29-Aug-2021
Date of Web Publication26-Sep-2022

Correspondence Address:
Hella Fiona Mathews
Department of Internal Medicine, JSS AHER, Mysore, Karnataka
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/aam.aam_65_21

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Background: Obesity and diabetes mellitus are two major factors related with the risk of metabolic syndrome and cardiovascular diseases. Co-existing hypertension with diabetes mellitus and obesity has poor prognosis for cardiovascular diseases. Ambulatory blood pressure monitoring (ABPM) correlates more closely to target organ damage than clinic blood pressure. Objectives: The objective of the study is to assess and compare ABPM pattern among obese and nonobese diabetes mellitus patients. Materials and Methods: A cross-sectional study was conducted among fifty obese and fifty nonobese diabetic patients who were classified based on their body mass index as per the WHO criterion. The clinical blood pressure measurements were measured on each subject using a digital sphygmomanometer, and 24 h ABPM was done and ABPM parameters such as dipping pattern, 24 h systolic blood pressure (SBP), diastolic blood pressure (DBP), Mean SBP, mean DBP, diurnal variability of SBP, DBP, Mean arterial pressure, pulse pressure, SD systole (Standard Deviation systole), SD diastole, white coat hypertension was derived and compared between the two groups. Results: Around 37 (74%) obese and 18 (36%) nonobese showed non dipping pattern in SBP and 28 (66.7%) of obese and 14 (33.3%) of nonobese showed a nondipping pattern in DBP and was found to be statistically significant (P < 0.001). On comparison between normotensive obese and normotensive nonobese, it was found that SBP non dipping pattern18 (67%) versus 9 (29%) and DBP nondipping pattern 12 (45%) versus 5 (16%) was statistically significant with P = 0.004, 0.016, respectively. Conclusion: Obese diabetes mellitus subjects had altered ABPM parameters and increased prevalence of nondipping status. In addition, obese diabetic patients who did not give prior history of hypertension were also found to have higher nondipping SBP and DBP patterns.

Keywords: Ambulatory blood pressure monitoring, blood pressure variability, diabetes mellitus, hypertension, nondipping, obesity

How to cite this article:
Mathews HF, Kumar S, Madhu B, Gona OJ, Srinath K M. The ambulatory blood pressure monitoring among obese and nonobese diabetes mellitus patients. Ann Afr Med 2022;21:255-61

How to cite this URL:
Mathews HF, Kumar S, Madhu B, Gona OJ, Srinath K M. The ambulatory blood pressure monitoring among obese and nonobese diabetes mellitus patients. Ann Afr Med [serial online] 2022 [cited 2023 Feb 6];21:255-61. Available from:

   Introduction Top

Obesity and diabetes mellitus are two major factors associated with the risk of metabolic syndrome and cardiovascular diseases. Patients with obesity and diabetes tend to have co-existing conditions such as dyslipidemia, sleep apnea, and hypertension.[1] Type 2 diabetes mellitus is frequently associated with hypertension, and it increases cardiovascular risk leading to cardiovascular damages such as silent cerebral infarcts and left ventricular hypertrophy and hence there is an emphasis on the tight blood pressure control to reduce cardiovascular events.[2]

Studies have indicated that the blood pressure monitored over a 24-h period is more accurate than clinic blood pressure in forecasting future cardiovascular events and target organ damage.[3] Health care professionals use ambulatory blood pressure monitoring (ABPM) as a noninvasive method to assess blood pressure reading over a 24- h period, when the patient is in his/her own living space and shows variations of the subject's blood pressure at different times of the day.

ABPM provides an opportunity to assess daytime, nighttime, 24-hr. BP, Morning BP surge, BP variability, and is regarded as one of the accurate methods for the diagnosis, assessment, and management of hypertension.[4]

International Diabetes Federation recommends that a 24-h ABPM can be used to identify white coat hypertension, masked hypertension, and to avoid overdiagnosis of hypertension.[5] When the BP variability is very large, it is generally very difficult to assess the exact blood pressure level. In such instances, a 24-h ABPM is advisable for the assessment of actual blood pressure level.[6]

ABPM also determines whether the person is a reverse dipper (<0%), nondipper (0%–10%), dipper (10%–20%), or extreme dipper (>20%) in blood pressure.[7],[8] Nondipping status indicates target organ damage in patients or nonefficient antihypertensive drug treatment.[2] Hence, we aimed to assess ABPM pattern in obese and nonobese diabetes mellitus subjects and compared the parameters across the two groups.


  1. To assess and compare ABPM pattern among obese and nonobese diabetes mellitus patients.

   Materials and Methods Top

Study design

A cross-sectional study was conducted among diabetic patients attending the OPD or admitted as in patients to the Department of General Medicine at a tertiary care hospital from June 2017 to August 2017.

A nonprobabilistic sampling technique was adopted, and all consecutive diabetic patients attending either outpatient or inpatient during the study period were enrolled and ensured that nearly equal proportion of age- and gender-matched obese and nonobese diabetic patients were included in the study.

The sample size for the study was calculated using the formula:

(4 pq/l2)

Where P = prevalence of hypertension among diabetics (which is considered to be 40% and q = (100–p) = 60% and l is the allowable error, i.e. considered as 10%, substituting the above values in the formula 4 × 40 × 60/10 × 10 = 96. Thus, the final sample size of 100 diabetic patients was considered for the study. Further considering noncompliance to 24 h blood pressure monitoring among subjects an additional 50 subjects was enrolled into the study.


Inclusion criteria

Fasting blood sugar (FBS) levels of more than 126 mg/dl, or random blood sugar of more than 200 mg/dl and/or HbA1c of more than 6.5%, and/or patients on anti-diabetic medication were considered to be diagnosed as diabetes mellitus.[7]

Exclusion criteria

Night shift workers, critically ill patients and patients who were not resting or sleeping adequately (minimum of 6–8 h of sleep) were excluded from the study.

Anthropometric measurements

Weight, height, and waist circumference were measured for all the patients. body mass index (BMI) was calculated using the formula weight (kg)/(height in meters)2. Based on the BMI criteria of WHO for the Asian population, the study subjects were categorized as obese (BMI >25) and nonobese (BMI <25).[9],[10]

Institutional ethics committee approved the study protocol, and the patients were explained regarding the study procedure and importance of the ABPM before recruiting into the study.

After obtaining the informed consent from each study participant, a pretested questionnaire was used to obtain the socio-demographic and clinical details of the study subjects. This included age, gender, height, weight, BMI, waist circumference, duration of diabetes, and medication details.

Office blood pressure measurement

The standard cuff was applied around the nondominant arm on each subject, and a digital sphygmomanometer (OMRON) was used to assess clinical blood pressure measurements. Measurements were taken with the participant in a sitting position after resting for 15 min. A single person did all the digital blood pressure measurements to avoid bias.

Ambulatory blood pressure monitoring

All subjects underwent 24-h ABPM on a usual working day. Four ABPM apparatus of MEDITECH company were used in the study. Appropriate size of cuff (large adult) was tied around the nondominant arm, and readings were obtained automatically at 30-min intervals throughout the day from 06.00 am to 10.00 pm and 1-h intervals throughout the night from 10.00 pm to 06.00 am. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) measurements along with the related time of measurements, were used to calculate blood pressure patterns. All the subjects were instructed to rest or sleep between 10.00 pm and 06.00 am (nighttime) and to maintain their usual activities between 06.00 am and 10.00 pm (daytime). The readings from ABPM instruments were in the form of graphs, charts, and tables [Figure 1].
Figure 1: Patient enrollment process

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A total of 150 diabetic patients were subjected to ABPM monitoring. The patients were asked to keep the BP cuff on their nondominant arm for 24 h. It disturbed their sleep as it measured blood pressure every half an hour in the daytime and every hour in the night. It also affected their daily living activities. Wearing the BP cuff for 24 h also created a sense of being under observation, which prevented them from completing the ABPM. Patients also complained of pain in their arms, which made them remove the apparatus before the completion of 24 h. Finally, 20 obese and thirty nonobese subjects did not complete the 24 h blood pressure recording and hence these subjects were not considered for the analysis.

Hypertension is diagnosed by 24-h ABPM when one or more of these criteria exist. The 20-h average BP is >130/80 mmHg, and the daytime average >135/85 mmHg, and/or night-time average >120/70 mmHg.[11] The dipping pattern demonstrated during monitoring can be of 4 types, such as, reverse dippers, nondippers, dippers, and extreme dippers. The reverse dipping is seen when the value is <0%. It indicates that the nocturnal blood pressure is higher than the diurnal blood pressure. The normal dipping is seen when the value is between 10% and 20%. Usually, normal people show a systolic dip in blood pressure at night. The blood pressure load is the percentage or proportion of readings which are higher than a predetermined level in 24 h. According to the recommendations of the National Institute for Health and Care Excellence (NICE) there is a minimum of two measurements per hour during a subject's usual waking hours (e.g., between 08.00 and 22.00 h). The NICE recommends the use of the average value of at least 14 measurements taken during a subject's usual waking hours to ascertain the diagnosis of hypertension.[12]

Based on the data obtained from the ABPM as shown in [Figure 2] and [Figure 3], the BP variability, dipping status, circadian pattern of blood pressure, morning surge in blood pressure, and changes in pulse pressure were recorded.
Figure 2: Dipping pattern in SBP among subjects

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Figure 3: Dipping pattern in diastolic blood pressure (among subjects)

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Ethical aspects

The Institutional Ethical Committee of the medical college and hospital approved the study.

Statistical analysis

All the data were analyzed using the SPSS 22 (Statistical program for Social sciences (SPSS) software version 22.0; SPSS Inc., Chicago, IL, USA). Descriptive statistics such as the mean and standard deviation was used to describe the main variables, and all the variables were normally distributed, the differences in variables between groups were evaluated using the t-test. For categorical variables, percentages were calculated to compare the relationship of these parameters with obesity, and the Chi-square test was applied. The study considered a two-sided P < 0.05 to be statistically significant.

   Results Top

A total of 100 patients completed the study fulfilling the essential requirements for the ABPM. [Table 1] describes the comparison of clinical characteristics, anthropometric measurements among obese and nonobese subjects. We observed that the proportion of males and females in obese group (54% vs. 46%) and nonobese (58% vs. 48%) and was not statistically not different. Majority (34%) of the obese diabetic were above 60 years; however, the proportion of obese and nonobese subjects across different age categories was not significant. The mean age among obese subjects was 54 ± 11.67 years, and among nonobese was 52.62 ± 11.93 years. It also describes the comparison of anthropometric parameters between the obese and nonobese study subjects like, weight (76.62 ± 9.01 vs. 61.22 ± 7.0) BMI (29.98 ± 3.49 vs. 22.70 ± 2.0) Abdominal circumference (106.50 ± 8.25 vs. 91.72 ± 10.27) and waist circumference (112.10 ± 8.56 vs. 96.88 ± 10.48) which were higher in obese group than nonobese and height (159.42 ± 6.5 vs. 164.23 ± 8.75) was lower among obese than nonobese. BMI value was statistically significant. The proportion of diabetic subjects based on the duration of diabetes mellitus was not significant, and the mean FBS was 194.26 ± 79.04 vs. 191.76 ± 63.1 mg/dl among obese and nonobese, respectively. Ninety percent of the obese and nonobese patients had uncontrolled diabetes mellitus with the FBS more than 126 mg/dl.
Table 1: Comparison of clinical characteristics and anthropometric measurements among obese and nonobese diabetes mellitus subjects

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[Table 2] compares ABPM parameters among the two study groups. The systolic nondippers were found to be 74% in obese versus 36% in nonobese, and this was statistically significant with P < 0.001. Similarly, DBP non dipping pattern was found to be 66.7% among obese versus 33.3% among nonobese with P < 0.001. We also observed that night load mean DBP is higher in obese than nonobese (76.50 ± 13.36 vs. 74.04 ± 9.44 and P < 0.05).Whitecoat hypertension was 44% versus 18% among obese and nonobese, and it was statistically significant with P < 0.05. Mean DBP night load was (76.50 ± 13.36 vs. 74.04 ± 9.44) and P < 0.05 and was statistically significant.
Table 2: Comparison of blood pressure patterns among obese and nonobese diabetes mellitus patients

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[Table 3] describes the comparison of ABPM parameters among hypertensives obese versus hypertensive nonobese and normotensive obese versu normotensive nonobese. We have observed that proportion of SBP nondipper is 82% among hypertensive obese versu 42% among hypertesnvise nonobese, P = 0.018.Mean office night SBP was higher among normotensive obese than normotensive nonobese (124.65 ± 16.70 vs. 116 ± 12.81, P = 0.037) and proportion of SBP nondipper was 67% among normotensive obese versus 29% normotensive nonobese. DBP nondipper was 45% versu 16% among normotensive obese and normotensive nonobese respectively, P = 0.016. Pulse pressure was also higher among normotensive obese than nonobese (26% vs. 6%, P = 0.03)
Table 3: Comparison of ambulatory blood pressure monitoring parameters among hypertensive obese, nonobese and normotensive obese and nonobese

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[Figure 2] mentions the comparison of dipping patterns in SBP among study subjects. [Figure 3] mentions the dipping pattern in DBP among subjects. [Figure 4] and [Figure 5] shows a dipping pattern in blood pressure in hypertensive obese, nonobese and normotensive obese, nonobese patients.
Figure 4: Dipping pattern in BP among hypertensive obese and nonobese subjects

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Figure 5: Dipping pattern in BP among normotensive obese and nonobese subjects

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   Discussion Top

Diabesity is a term used to combinedly describe the health effects of obesity and diabetes mellitus. The dual epidemic of obesity and diabetes mellitus is growing rapidly, causing an important public health issue. It is estimated that the number of adults individuals <40 years with obesity would increase sixfold times, and diabetes mellitus is projected to be affecting more than six hundred million by 2040.[13]

Co-existing obesity along with diabetes have shown to have more target organ damage and cardiovascular diseases. High blood pressure affects majority of patients with diabetes and is known to be associated with long-term adverse events Studies have also found that Asians have an ethnic and genetic vulnerability for diabetes mellitus and lower thresholds for CVD risk factors.

Consequently, when compared to the Western population, Asians develop diabetes mellitus at a younger age with a lower BMI and waist circumference. Hence, the lean Indian adults with a lower BMI may be relatively at equal risk of CVD than those who are obese. So early identification of abnormalities in blood pressure would enable the progression of atherosclerosis and ischemic heart disease.[14]

In the present study, obese and nonobese subject's age and sex nearly pair-matched among obese and nonobese diabetes mellitus subjects and comparison of anthropometric measurements have shown that the mean BMI among obese diabetic patients was found to be 29.98 ± 3.49 and among nonobese was 22.70 ± 2.05 and the difference was statistically significant (<0.001). Similar observation was made in several other studies where the BMI among diabetic patients was found to range between 26.66 and 29.12 kg/m2. Indicating the Indian population have lower BMI associated with diabetes than Western counterparts. The mean BMI among diabetic patients was found to be similar to this study by akholar et al., (26.33 ± 4.74 kg/m2)[15] and this was further confirmed with Dambal et al., (28.83 ± 5.87 kg/m2).[16]

In our study, the mean WC among the obese diabetic subjects was found to be 112.10 ± 8.56 and among nonobese diabetic subjects was 96.88 ± 10.48. In comparison to the results our study Akholar et al., and Dambal et al., had reported a lower WC of 96.08 ± 11.09 and 92.46 ± 10.23 in the obese diabetic subjects and 96.88 ± 10.48, in the nonobese diabetic subjects.[15],[16] The obese diabetes subjects were short-statured compared to the nonobese diabetic subjects in our study (height: 159.42 ± 6.5 vs. 164.23 ± 8.75 cms, P = 0.038). Short stature could be one of the reasons for Asians to have higher risk of diabetes and cardiovascular diseases even with lower BMI when compared to their Western counterparts. The WHO cut off of obesity for western population is more than 30 kg/m2 however we have observed that the mean BMI of obese diabetes mellitus was 29.98 ± 3.9.[17]

ABPM is a fully automated technique with multiple BP measurements taken at regular intervals (every 20–30 min over 24-48-h period) while the patient is in normal daily activities. Hypertension in the presence of obesity and diabetes mellitus has a higher risk for CVD and currently 24 h. ABPM is advised in individuals with resistant hypertension. As compared to the office blood pressure monitoring, many studies have shown that the ABPM is a better predictor of the hypertension-mediated organ damage.[18] Understanding the ABPM profile depends on parameters, such as daytime, night-time, and 24-h bp measurements.[19]

In the present study, the SBP non dipping parameters were found to be higher in obese diabetes subjects (nondipper: 37 (74%) vs. 18 (36%), Dipper: 6 (12%) vs. 23 (46%), Raiser: 7 (14%) vs. 9 (18%), P < 0.001) when compared to nonobese and DBP (nondipper: 28 (66.7%) vs. 14 (33.3%), Dipper: 13 (31%) vs. 29 (69%), Raiser: 9 (56.3%) vs. 7 (43.8), P < 0.001) nondipping in both groups indicates that obese patients were at greater risk of BP variability. In a study done by Ukkola et al., assessing the nondipping pattern in ABPM in middle age subject without known hypertension or T2DM found that normal dipping status was more common among subjects with metabolic syndrome (P < 0.001) impaired glucose tolerance and ABPM nondipping status was an independent predictor of IGT in multivariate models.[20]

Earlier data have also provided evidence that there might be an inter-relationship between Metabolic syndrome, enhanced sodium sensitivity of blood pressure and nondipping pattern.

A similar non dipping was observed in a study conducted by Hassan et al.[21] among Arabs of Homan family study where they observed 50% of nondippers were having metabolic syndrome and the daytime, nighttime SBP, DBP, and night time PP were significantly higher in nondipper subjects with metabolic syndrome and an important determinant of nondipping Blood pressure was high BMI and high serum triglycerides.

In addition, the mean SBP parameters (mmHg) was higher in diabetic obese subjects than diabetic nonobese subjects (mean office SBP: 142.78 ± 24.13 vs. 138.88 ± 27.03), (mean SBP -24 h: 136.78 ± 19.50 vs. 132.32 ± 19.29], (mean SBP – day load: 138.08 ± 19.65 vs. 134.86 ± 19.82), [mean SBP – night load: 133.22 ± 20.77 vs. 125.90 ± 19.76), [mean SBP dip: 3.33 ± 6.84 vs. 6.37 ± 8.03) which was not statistically significant. All the mean SBP parameters were found to be higher among diabetic obese patients but significance could not be found probably because of the sample size and nominal differences among SBP parameters in both the groups. However, the statistically significant differences have been found among mean DBP -load at night in both the groups (76.50 ± 13.36 vs. 74.04 ± 9.44, P < 0.05). The possible underlying pathogenic mechanisms in the impaired BP decline during night include extrinsic and intrinsic factors such as abnormal neurohormonal regulation, lack of physical activity, and increased dietary sodium intake as described by Kanbay et al.[22]

Ayala et al. demonstrated a large circadian blood pressure variability (P < 0.001) among large Spanish population which was found to be significantly higher in obese diabetes patients.[23] Flores et al.,[24] also showed that nondipping status was common in normotensive patients, but in severely obese patients, glucose tolerance abnormalities were primarily associated with impaired nocturnal BP fall.

Thus, the present study demonstrates that as BMI increases, both the systolic and diastolic pressure increase, and the day and night systolic BP load also increase. Similar studies in different population have revealed that as the BMI increases, both systolic and diastolic load also increase.[25] Similar to the present study, Araujo et al. reported a significant increase in nondippers, and reverse-dippers in overweight and obese individuals with increased incidence of fatal and nonfatal cardiovascular events.


Since the study was a short-term study conducted for 2 months, the complications such as microvascular complications associated with hypertension, diabetes mellitus, and obesity could not be assessed. Bias as a result of hospital-based study and its limitation in generalizing the findings to other population, cross-sectional study, small sample size, and the lack of follow-up data have also been some of the limitations of the present study.

   Conclusion Top

The present study confirms that there was a significant circadian variation of blood pressure among obese diabetes mellitus subjects. Nondipping pattern in blood pressure was significantly observed among obese diabetes subjects irrespective of being a hypertensive or a normotensive. ABPM to be considered in the management and follow-up of patients with diabetes mellitus.


Special thanks to the Department of Medicine.

Financial support and sponsorship

The research was funded and approved by ICMR as part of STS program in 2017 (Reference ID-2017-05625).

Conflicts of interest

There are no conflicts of interest.

   References Top

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Staessen JA, Bieniaszewski L, O'Brien E, Gosse P, Hayashi H, Imai Y, et al. Nocturnal blood pressure fall on ambulatory monitoring in a large international database. The “Ad Hoc' Working Group. Hypertension 1997;29:30-9.  Back to cited text no. 11
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Akholkar PJ, Gandhi AA. Prevalence of obesity in diabetic and non-diabetic population. IMSEAR ID: sea-166426 ,2015.  Back to cited text no. 15
Dambal A, Herur A, Padaki S, Patil S, Manjula R, Chinagudi S, et al. The correlation of the duration of diabetes with anthropometric indices in type-2 diabetes mellitus. J Clin Diagn Res 2011;5:257-9.  Back to cited text no. 16
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Ramachandran A, Snehalatha C, Shetty AS, Nanditha A. Trends in prevalence of diabetes in Asian countries. World J Diabetes 2012;3:110-7.  Back to cited text no. 19
Ukkola O, Vasunta RL, Kesäniemi YA. Non-dipping pattern in ambulatory blood pressure monitoring is associated with metabolic abnormalities in a random sample of middle-aged subjects. Hypertens Res 2009;32:1022-7.  Back to cited text no. 20
Hassan MO, Jaju D, Albarwani S, Al-Yahyaee S, Al-Hadabi S, Lopez-Alvarenga JC, et al. Non-dipping blood pressure in the metabolic syndrome among Arabs of the Oman family study. Obesity 2007;15:2445-53.  Back to cited text no. 21
Kanbay M, Turgut F, Uyar ME, Akcay A, Covic A. Causes and mechanisms of nondipping hypertension. Clin Exp Hypertens 2008;30:585-97.  Back to cited text no. 22
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  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]

  [Table 1], [Table 2], [Table 3]


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