Occurrence of Cardio Metabolic Risk and Attitude Towards Reduction of Cardio Metabolic Risk Factors Among Patient Receiving Long Term Anti Psychotics

Surya Prakash; Nanda Kumar Paniyadi; Bishwa Ranjan Mishra; Asha Prabhakar Shetty

doi:10.4103/IOPN.IOPN_17_20

ORIGINAL ARTICLE

Year : 2020 | Volume : 17 | Issue : 2 | Page : 64-71

Occurrence of Cardio Metabolic Risk and Attitude Towards Reduction of Cardio Metabolic Risk Factors Among Patient Receiving Long Term Anti Psychotics

Surya Prakash, Nanda Kumar Paniyadi, Bishwa Ranjan Mishra, Asha Prabhakar Shetty
Department of Nursing, College of Nursing, AIIMS, Bhubaneswar, Odisha, India

Date of Submission	29-Jun-2020
Date of Decision	09-Jul-2020
Date of Acceptance	11-Aug-2020
Date of Web Publication	08-Feb-2021

Correspondence Address:
Mr. Nanda Kumar Paniyadi
College of Nursing, AIIMS, Bhubaneswar - 751 019, Odisha
India
Mr. Surya Prakash
College of Nursing, AIIMS, Bhubaneswar - 19, Odisha
India

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/IOPN.IOPN_17_20

Abstract

Background: Noncommunicable disorders (NCDs) are in an increasing trend over the past decades. The increased risk of CMD may be due to various modifiable factors. The use of antipsychotics in patients with severe mental illness (SMI) also increase the risk of CMD. Thus, monitoring and assessing the risk factors is quite essential in a clinical setting. Regular monitoring and attitude of the patients toward the reduction also plays an essential role in the reduction of CMR factors. Objectives: 1. To estimate the prevalence of CMR among patients receiving long term antipsychotics 2. To assess the attitude toward the reduction of CMR factors among patients receiving long term antipsychotics Materials and Methods: A cross sectional observational study using convenient sampling technique was used. The sample size was 110. A semi-structured questionnaire was used. The data were analyzed by descriptive statistics (frequency, percentage, mean, standard deviation, median, and interquartile range) and inferential statistics (Chi-square). Results: It was found that majority of the patients (51.8%) are a low risk for CMD and 91.8% of the patients had favorable attitude toward risk reduction of cardiometabolic disease. A significant association was found between attitude and age (P = 0.001*), religion (P =0.003*), and socioeconomic status (P = 0.03*). Conclusion: In this study, it was found that the risk of developing cardiometabolic disease is found in all patients ranging from low to high risk. Meanwhile, the attitude toward reduction was positive.

Keywords: Antipsychotics, attitude, cardiometabolic risk, severe mental illness

How to cite this article:
Prakash S, Paniyadi NK, Mishra BR, Shetty AP. Occurrence of Cardio Metabolic Risk and Attitude Towards Reduction of Cardio Metabolic Risk Factors Among Patient Receiving Long Term Anti Psychotics. Indian J Psy Nsg 2020;17:64-71

How to cite this URL:
Prakash S, Paniyadi NK, Mishra BR, Shetty AP. Occurrence of Cardio Metabolic Risk and Attitude Towards Reduction of Cardio Metabolic Risk Factors Among Patient Receiving Long Term Anti Psychotics. Indian J Psy Nsg [serial online] 2020 [cited 2023 Mar 21];17:64-71. Available from: https://www.ijpn.in/text.asp?2020/17/2/64/308826

Introduction

Noncommunicable disorders (NCDs) are in an increasing trend over the past decades. Among the NCDs, cardiometabolic disorder (CMD) is one among them.^[1]

The global burden of disease of the cardiovascular disorder (CVD) death rate is 272 per 100,000 population in India, which is higher than the global average of 235 per 100,000 population.^[2] The factors attributing to the increased risk of CMD include low socioeconomic status, physical inactivity, poor dietary habits, smoking, and the use of antipsychotic medications.^[2],[3] Lifestyle modifications such as physical activity, healthy eating habits, and weight control are the first line of intervention to control the CMD. It also focuses on behavioral change strategies.^[3]

Severe mental illness (SMI) is often defined by its length of duration and the disability it produces. These illnesses include disorders such as schizophrenia, schizoaffective disorders, and severe forms of mood disorders.^[4] SMI is one of the clinical concerns as individuals who are suffering from SMI are at higher risk for developing CMD.^{[1],[4],[5],[6]} The illness and the treatment with antipsychotics increased the chances of mortality and also with a higher risk for the development of the CMD.^[7] A study done in Kashmir shows the prevalence rate of 37.74% among psychiatric inpatient.^[8] The attitude of the patients toward the reduction also plays an essential role in the reduction of cardiometabolic risk (CMR) factors.^[6],[9],[10]

The increased risk of CMD may be due to various modifiable factors such as physical inactivity, unhealthy diets, and sedentary lifestyle. The patients and the caregiver probably ignore behavioral and lifestyle modification. Combinations of antipsychotics also increase the risk of CMD. Thus, monitoring and assessing the risk factors are quite essential in a clinical setting. Regular monitoring of the risk can lead to early identification of the risk factors, and appropriate intervention can be provided. The attitude of the patients toward the reduction also plays an essential role in the reduction of CMR factors.

Thus, to know about the prevalence of CMR factors among patients with SMI on long-term antipsychotic seeking treatment in the Psychiatric Outpatient Department (OPD) of AIIMS, Bhubaneswar, the study was undertaken by the investigator. It also focuses on assessing the attitude of the patients with SMI toward the reduction of the CMR factors.

Objectives of the study

Objectives

To estimate the prevalence of CMR among patients receiving long-term antipsychotics
To assess the attitude toward the reduction of CMR factors among patients receiving long-term antipsychotics
To find the association between CMR and sociodemographic variables
To find the association between attitude and sociodemographic variables.

HYPOTHESIS (level of significance P < 0.05):

H₀₁: There is a significant association between CMR and sociodemographic variables
H₀₂: There is a significant association between attitude toward CMR reduction and sociodemographic variables.

Operational definition

Cardiometabolic risk

It refers to risk factors that increase the likelihood of experiencing cardiovascular events or developing diabetes. Risk of developing Cardio Metabolic Disorders (CMD) are identified by dyslipidemia, hypertension, pre-diabetic, abdominal obesity, physical inactivity and family history of comorbid substance use (Tobacco, Alcohol etc). All parameters are assessed by patient history, anthropometric measurement (height, weight, body mass index, and waist circumference), blood pressure, and blood investigation (lipid profile, fasting blood sugar, and C reactive protein).

Attitude toward risk reduction

It is the belief and reaction towards cardiometabolic risk reduction as measured by 3- point attitude (Likert) scale.

Materials and Methods

This was a cross-sectional observational study that was conducted in the psychiatry OPD of a tertiary care hospital in Odisha. A convenient sampling technique was used to select the sample. The age group between 18 and 65 years and diagnosed by the psychiatrist as per the ICD-10 criteria as SMI were included in the study. Patients who are suffering from SMI and continuous antipsychotic treatment more than 1 year and who can understand Hindi, able to read and write Odiya, and English are included in the study. The exclusion criteria of the study were patients with a history of intellectual disability or dementia and not willing to participate. The sample size was 110, estimated based on the previous studies, where 80% precision. The tool used in the study was a semistructured questionnaire prepared by the researcher which was validated by seven experts from different fields. The content validity was assessed. The reliability of the tools was assessed by administering the tools to twenty patients. The Cronbach's alpha score was 0.648. The total time for administration of the tools is 30–45 min. The tools consist of three parts: sociodemographic proforma, investigator's CMR assessment tool, and CMR reduction attitude scale. The sociodemographic proforma include age, gender, religion, educational qualification, occupational health, marital status, place of living, monthly income, socioeconomic status, and clinical variables of the patients such as duration of mental illness, duration of antipsychotics, psychiatric diagnosis, current antipsychotic medication, medical and substance comorbidities, and family history of cardiometabolic disease. CMR assessment tool consists of 13 items. The first five items describe high-risk factors and are scored as 0 (no risk), 1 (low risk), and 2 (high risk). The other eight items describe the low-risk factor which is scored as 0 (no risk), 0.5 (low risk), and 1 (high risk). The overall score is classified as high risk (13–18), moderate risk (7–12), low risk (1–6), and no risk (0). CMR reduction attitude scale was a 3-point Likert scale, which consists of 22 items, and the score ranges from 22 to 66. It is interpreted as a favorable attitude (score 45–66) and an unfavorable attitude (score 22–44). The data were analyzed by descriptive statistics (frequency, percentage, mean, standard deviation, median, and interquartile range) and inferential statistics (Chi-square). Ethical permission was obtained from the Institutional Ethics Committee from where the study was conducted (Ref. no. IEC/AIIMS BBSR/NUR/2019-20/01). Written consent from the participants was obtained before data collection.

Results

In this study, we recruited 110 patients who are on long-term antipsychotics. Data collected from September 2019 to February 2020 were the period of data collection. The sociodemographic characteristics are depicted in [Table 1], in which most of the patients (38.2%) belong to the age group between 18 and 30 years and 68.2% are males, 48.2% were married, 60.9% belonged to the rural area, 32.6% had predegree/diploma (11^th–12^th standard), and 23.6% were self-employed.

Table 1: Frequency and percentage distribution of sociodemographic characteristics of the patients (n=110)

Click here to view

The values not shown in the pie diagram

[Figure 1] shows the psychiatric diagnosis of the patients. About 49.1% (54) of the patients were diagnosed with schizophrenia, 31.8% (35) diagnosed with bipolar affective disorder (BPAD), and 19.1% (21) diagnosed with depression.

Figure 1: Pie diagram showing the diagnosis of the patients

Click here to view

[Table 2]: Shows the current prescribed antipsychotics medication among the subjects.

Table 2: Frequency and percentage distribution of patients as per their current antipsychotic medication (n=110)

Click here to view

[Table 3] shows the comorbid medical illness and substance used among the patients with long-term antipsychotic use. Diabetes mellitus (DM) (17.3%) was the most common medical comorbidities among the patients and the use of smokeless tobacco (33.6%) was the most common substance used among the patients.

Table 3: Frequency and percentage distribution of the patients as per their medical and substance use related comorbidities along with long-term antipsychotic use (n=110)

Click here to view

[Figure 2] shows that in the bar graph, x-axis shows the percentage of the patients with family history of various medical illnesses. The y-axis shows the different medical illnesses such as DM, CVD, and hypertension (HTN). It was found that 37.3% (41) had family history of DM, 20.9% (23) with cardiovascular disease, and 43.6% (48) had HTN.

Figure 2: Bar graph of family history of cardiometabolic disorders

Click here to view

Objective 1: To estimate the prevalence of CMR among patients receiving long-term antipsychotics.

[Table 4] shows CMR; the majority of the patients (51.8%) are a low risk for CMD.

Table 4: Distribution of cardiometabolic risk scores in terms of frequency and percentage (n=110)

Click here to view

Objective 2: To assess the attitude toward the reduction of CMR factors among patients receiving long-term antipsychotics.

[Table 5] shows that majority of the patients (101, 91.8%) had favorable attitude toward risk reduction of cardiometabolic disease which arises due to long-term antipsychotic use.

Table 5: Frequency and percentage distribution as per their attitude toward reduction of cardiometabolic risk (n=110)

Click here to view

Objective 3: To find the association between CMR and sociodemographic variables.

H₀₁: There is a significant association between CMR and sociodemographic variables.

In [Table 6], a significant association was found between CMR and age (P = 0.005*), marital status (P = 0.02*), and place of living (P = 0.03*). Thus, the research hypothesis states that there is a significant association between CMR and sociodemographic variables; H₀₁ was partially accepted.

Table 6: Association between sociodemographic characteristics of patients and cardiometabolic risk (n=110)

Click here to view

Objective 4 To find the association between attitude and sociodemographic variables.

H₀₂: There is a significant association between attitude toward CMR reduction and sociodemographic variables.

[Table 7] shows that a significant association was found between attitude and age (P = 0.001*), religion (P = 0.003*), and socioeconomic status (P = 0.03*).

Table 7: Association between sociodemographic characteristics of patients and attitude toward reduction of cardiometabolic risk (n=110)

Click here to view

Research hypotheses

There is an association between attitude toward CMR reduction and sociodemographic variables; H₀₂ was partially accepted.

Other findings Physiological parameters

Section II: Description of CMR factors.

[Table 8] shows other physiological parameter findings of the study.

Table 8: Frequency and percentage distribution of cardiometabolic factors among the patients with long term antipsychotics treatments (n=110)

Click here to view

Discussions

Sociodemographic characteristics

In this study, most of the patients (38.2%) belong to the age group between 18 and 30 years. The majority of the patients (68.2%) are male, 60.9% belonged to the rural area, and 31.8% have monthly income of 3908–11,707, and the socioeconomic status of more than half of the patients (55.5%) was above the poverty line. These findings are comparable with a hospital-based study conducted in Kashmir where the mean age of the patients was 38.26, and 42.26% of the patients were female and 57.74% were male, 59.6% were from a rural background, and 35.7% were from lower socioeconomic status.^[8]

Clinical profile characteristics

In this study, it was found that the median duration of mental illness of the patients was 4.25 years (range 1–41), whereas a study conducted in Hong Kong found that the mean duration of illness was 1–17 years (204.03 months).^[1]

In this study, it was found that 49.1% of the patients were diagnosed with schizophrenia, 31.8% of patients were BPAD, and 19.1% of patients were depression. These findings are comparable with a study conducted in Kashmir which reported that 39.45% were diagnosed as psychotic disorder, followed by BPAD 31% and 18.78% diagnosed as depression.^[8]

Treatment with antipsychotics

In this study, it was found that the majority of the patients were prescribed with second-generation antipsychotics. It is comparable with various studies conducted in Hong Kong, India, and Japan, which revealed that second-generation antipsychotics are prescribed more than the first-generation antipsychotics.^[3],[8],[11]

In this study, it was found that 38.2% of the patients prescribed with olanzapine, 4.3% with aripiprazole, and 3.6% with clozapine, 30% of the patients prescribed with risperidone, 22.7% of the patients prescribed quetiapine, and 20.9% of the patients prescribed amisulpride. These findings are comparable with a population-based study conducted in the UK which reported 23.20% subject prescribed with olanzapine, 6.10% aripiprazole, 0.80% clozapine, 16.40% risperidone, 35.80% quetiapine, 4.20% amisulprode(12).^[12] Another study conducted in Hong Kong revealed that the common antipsychotics prescribed to the patients were 19.5% olanzapine, 11% risperidone, 8.5% quetiapine, 4.9% amisulpride, 2.4% aripiprazole, and 17.1% clozapine.^[1]

In this study, it was found that 12 patients (10.9%) were prescribed with first-generation antipsychotics, which was haloperidol in combination with second-generation antipsychotics. These findings are comparable with a few studies which reported. The combination of first generation and second generation antipsychotics are effective ranging from 14.6% to 36.5% among the patients.

Characteristics of comorbidities

In this study, it was found that there are medical comorbidities among the patients (17.3%) with Type II DM, 14.5% with HTN, 8.2% with hypothyroidism, 4.5% with cardiovascular disease, and 2.7% were diagnosed with polycystic ovarian disease (female). These findings are comparable with a study conducted in Singapore, where 11.1% of the patients were Type-II DM, 41.7% CVD, and 30.6% were HTN.^[13] Another study in the UK also reported that 11.9% of the patients were diagnosed as Type 2 DM and 20.2% diagnosed with HTN.^[12]

In the present study, it was found that comorbidity of substance use among patients was 33.6% of the patients were smokeless tobacco users, 8.2% of the patients were tobacco smokers, and 10.9% of patients were alcohol users. Similar findings were reported in a similar study conducted in Assam, where 68.2% of the patients used tobacco and 40.9% of the patients used alcohol.^[5] Another study conducted in Singapore reported that 69.7% of the patients have a history of smoking.^[13] A study conducted in Hong Kong reported that 6.1% of the patients were light smoker (<10 per day), 13.4% of the patients were moderate smoker (10–19 per day), and 18.3% as a heavy smoker (>20 per day).^[1]

In this study, it was found that 43.6% of patients had a family history of HTN, 37.3% of patients had a family history of DM, and 20.9% of patients had a family history of cardiovascular diseases. These findings are consistent with the study conducted in Assam, which reported that 68.2% of the patients had a family history of DM/CVD/HTN.^[5]

Prevalence of cardiometabolic risk

In the present study, it was found that the majority of the patients (51.8%) had a low risk for CMD, 47.3% of the patients had moderate risk for CMD, and 0.9% of the patients had a high risk for CMD. There were no patients without any risk for CMD. These findings are consistent with several findings that reported that the overall prevalence of cardiometabolic syndrome (34.74%) was in Kashmir,^[8] 29% was in Hong Kong,^[1] 29.3% in Assam.^[5]

Attitude toward the reduction of cardiometabolic risk factors

In this study, we found that 91.8% of the patients were having a favorable attitude toward the reduction of CMR, and only 8.2% of patients had an unfavorable attitude. Similar findings conducted in Rajasthan, where having 76.1% of the patients have a high mean attitude.^[14] In a study conducted in Sri Lanka, it was found that 78.01% of the patients have a high mean attitude score.^[15] Another study in Turkey reported that 42.8% of the patients are having a good attitude toward the reduction of CMR.^[16]

Implication of the study

Nurses can provide psychoeducation to the patient and their family members to improve the quality of life and reduce the CMR due to the use of antipsychotic agents for prolong periods and bring changes in the attitude toward the reduction of CMR among all SMI patients under their care. Intervention module for reducing modifiable CMR factors for nurses can be developed for their patients in the clinical setup. Nurses can be trained in the assessment of CMR factors and graded accordingly as their routine practice.

Recommendation

A similar study can be done with CMR reduction intervention
More extensive research in the area of long-term antipsychotic use patients may be done to find the other risk factors
Intervention module for the reduction of CMR can be developed and exerted on patients with long-term antipsychotics use.

Conclusion

The individual with SMI has increased chances for developing cardiometabolic disease. The treatment with antipsychotic medications further increases the risk of developing cardiometabolic disease. In this study, it was found that the risk of developing cardiometabolic disease is found in all patients ranging from low to high risk. Meanwhile, the attitude toward reduction was positive. Further, the management of the CMR can be taken into consideration.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

References

1.	Bressington D, Mui J, Tse ML, Gray R, Cheung EF, Chien WT. Cardiometabolic health, prescribed antipsychotics and health-related quality of life in people with schizophrenia-spectrum disorders: A cross-sectional study. BMC Psychiatry 2016;16:411.
2.	Prabhakaran D, Jeemon P. Global Burden of Cardiovascular Disease Cardiovascular Diseases in India; 2016. p. 1605-20.
3.	Wang Q, Chair SY, Wong EM, Taylor-Piliae RE, Qiu XCH, Li XM. Metabolic syndrome knowledge among adults with cardiometabolic risk factors: A cross-sectional study. Int J Environ Res Public Health 2019;16:1-10.
4.	Kibourne A.M., Brar J.S., Drayer R.A., Xu X. Cardiovascular disease and metabolic risk factors in male patients with schizophrenia, schizoaffective disorder, and bipolar disorder, .Psychosomatics;2007; 48: 412-417.
5.	Das D, Bora K, Baruah B, Konwar G. Prevalence and predictors of metabolic syndrome in schizophrenia patients from Assam. Indian J Psychiatry 2017;59:228-32. [PUBMED] [Full text]
6.	Ludwick JJ, Oosthuizen PP. Screening for and monitoring of cardio-metabolic risk factors in outpatients with severe mental illness in a primary care setting. Afr J Psychiatry (Johannesbg) 2009;12:287-92.
7.	Batsis JA, Lopez-Jimenez F. Cardiovascular risk assessment–from individual risk prediction to estimation of global risk and change in risk in the population. BMC Med 2010;8:29.
8.	Hussain T, Margoob MA, Shoib S, Shafat M, Chandel RK. Prevalence of Metabolic Syndrome among Psychiatric Inpatients: A Hospital Based Study from Kashmir. J Clin Diagn Res 2017;11:VC05-8.
9.	Lang DJ, Barr AM, Procyshyn RM. Management of medication-related cardiometabolic risk in patients with severe mental illness. Curr Cardiovasc Risk Rep 2013;7:283-7.
10.	Cooper SJ, Reynolds GP, With expert co-authors (in alphabetical order):, Barnes T, England E, Haddad PM, et al. BAP guidelines on the management of weight gain, metabolic disturbances and cardiovascular risk associated with psychosis and antipsychotic drug treatment. J Psychopharmacol 2016;30:717-48.
11.	Sugawara N, Yasui-Furukori N, Sato Y, Kishida I, Yamashita H, Saito M, et al. Comparison of prevalence of metabolic syndrome in hospital and community-based Japanese patients with schizophrenia. Ann Gen Psychiatry 2011;10:21.
12.	Collier A, Kessavalou K, Sit LE, Hair M, Cameron L. Anti-psychotic medication and the pattern of cardiovascular risk factors: A population based study (the ayrshire diabetes follow-up cohort [ADOC] study). J Addict Res Ther 2017;8:2.
13.	Seng L, Seow E, Chong SA, Wang P, Shafie S, Ong HL, et al. Science direct metabolic syndrome and cardiovascular risk among institutionalized patients with schizophrenia receiving long term tertiary care. Compr Psychiatry 2017;74:196-203.
14.	Verma A, Mehta S, Mehta A, Patyal A. Knowledge, attitude and practices toward health behavior and cardiovascular disease risk factors among the patients of metabolic syndrome in a teaching hospital in India. J Family Med Prim Care 2019;8:178-83. [PUBMED] [Full text]
15.	Amarasekara P, de Silva A, Swarnamali H, Senarath U, Katulanda P. Knowledge, attitudes, and practices on lifestyle and cardiovascular risk factors among metabolic syndrome patients in an urban tertiary care institute in Sri Lanka. Asia Pac J Public Health 2016;28:32S-40S.
16.	Tyas D, Phytanza P, Burhaein E, Aquatic activities as play therapy children Autism Spectrum Disorders, International Journal of Disabilities Sports and Health Sciences, 2019, vol-2, Issues-2, PNo- 64-71.