Body Mass Index Changes of Patients on Antipsychotics: A Comparison between Typical and Atypical Antipsychotics

Article Information

Chukwujekwu DC1, Olose OE2

1Department of Neuropsychiatry, University of Port Harcourt Teaching Hospital, Port Harcourt, Nigeria

2Department of Psychiatry, University of Calabar Teaching Hospital, Calabar, Nigeria

*Corresponding Author: Dr. Chukwujekwu DC, Department of Neuropsychiatry, University of Port Harcourt Teaching Hospital, Port Harcourt, Nigeria

Received: 26 January 2019; Accepted: 06 February 2019; Published: 10 February 2019

Citation: Chukwujekwu DC, Olose OE. Body Mass Index Changes of Patients on Antipsychotics: A Comparison between Typical and Atypical Antipsychotics. Journal of Psychiatry and Psychiatric Disorders 3 (2019): 006-013.

Share at Facebook

Abstract

Objectives:The study was designed to assess and compare the changes in the body mass index of patients on typical and atypical antipsychotics in a tertiary hospital in Nigeria.

Materials and Methods: Consenting psychiatric patients who were antipsychotic naive before the commencement of the study and who attended the hospital between February 2014 and October 2014 were enlisted in the study. The SCAN and a socio-demographic questionnaire were administered to the subjects. BMI of each subject was calculated before the administration of antipsychotic and after 1 month, 2 months and 3months intervals.

Results: 138 out of 140 subjects enlisted in the study were analyzed. The mean BMI changes derived were 23.7461 ± 3.58270, 25.0074 ± 3.99667, 25.960 ± 4.24540 and 27.1261 ± 4.66810. The atypical antipsychotics caused relatively higher mean BMI increases more than the typical ones and the mean BMl differences between the two groups of antipsychotic users is consistently statistically significant (df=l, F=48.354, p=0.000, df=I, F=51.082, P=0.000, df=I, F=77.451, p=0.000).

Conclusion: Considering the invaluable role of antipsychotics in the treatment of psychiatric patients, non-pharmacologic interventions are highly recommended to help control the weight of patients on antipsychotic treatment.

Keywords

Antipsychotic, Typical, Atypical, Body mass index, Weight gain

Antipsychotic articles Antipsychotic Research articles Antipsychotic review articles Antipsychotic PubMed articles Antipsychotic PubMed Central articles Antipsychotic 2023 articles Antipsychotic 2024 articles Antipsychotic Scopus articles Antipsychotic impact factor journals Antipsychotic Scopus journals Antipsychotic PubMed journals Antipsychotic medical journals Antipsychotic free journals Antipsychotic best journals Antipsychotic top journals Antipsychotic free medical journals Antipsychotic famous journals Antipsychotic Google Scholar indexed journals  Typical articles  Typical Research articles  Typical review articles  Typical PubMed articles  Typical PubMed Central articles  Typical 2023 articles  Typical 2024 articles  Typical Scopus articles  Typical impact factor journals  Typical Scopus journals  Typical PubMed journals  Typical medical journals  Typical free journals  Typical best journals  Typical top journals  Typical free medical journals  Typical famous journals  Typical Google Scholar indexed journals Atypical articles Atypical Research articles Atypical review articles Atypical PubMed articles Atypical PubMed Central articles Atypical 2023 articles Atypical 2024 articles Atypical Scopus articles Atypical impact factor journals Atypical Scopus journals Atypical PubMed journals Atypical medical journals Atypical free journals Atypical best journals Atypical top journals Atypical free medical journals Atypical famous journals Atypical Google Scholar indexed journals Body mass index articles Body mass index Research articles Body mass index review articles Body mass index PubMed articles Body mass index PubMed Central articles Body mass index 2023 articles Body mass index 2024 articles Body mass index Scopus articles Body mass index impact factor journals Body mass index Scopus journals Body mass index PubMed journals Body mass index medical journals Body mass index free journals Body mass index best journals Body mass index top journals Body mass index free medical journals Body mass index famous journals Body mass index Google Scholar indexed journals Weight gain articles Weight gain Research articles Weight gain review articles Weight gain PubMed articles Weight gain PubMed Central articles Weight gain 2023 articles Weight gain 2024 articles Weight gain Scopus articles Weight gain impact factor journals Weight gain Scopus journals Weight gain PubMed journals Weight gain medical journals Weight gain free journals Weight gain best journals Weight gain top journals Weight gain free medical journals Weight gain famous journals Weight gain Google Scholar indexed journals socio-demographic articles socio-demographic Research articles socio-demographic review articles socio-demographic PubMed articles socio-demographic PubMed Central articles socio-demographic 2023 articles socio-demographic 2024 articles socio-demographic Scopus articles socio-demographic impact factor journals socio-demographic Scopus journals socio-demographic PubMed journals socio-demographic medical journals socio-demographic free journals socio-demographic best journals socio-demographic top journals socio-demographic free medical journals socio-demographic famous journals socio-demographic Google Scholar indexed journals non-pharmacologic interventions articles non-pharmacologic interventions Research articles non-pharmacologic interventions review articles non-pharmacologic interventions PubMed articles non-pharmacologic interventions PubMed Central articles non-pharmacologic interventions 2023 articles non-pharmacologic interventions 2024 articles non-pharmacologic interventions Scopus articles non-pharmacologic interventions impact factor journals non-pharmacologic interventions Scopus journals non-pharmacologic interventions PubMed journals non-pharmacologic interventions medical journals non-pharmacologic interventions free journals non-pharmacologic interventions best journals non-pharmacologic interventions top journals non-pharmacologic interventions free medical journals non-pharmacologic interventions famous journals non-pharmacologic interventions Google Scholar indexed journals hypertension articles hypertension Research articles hypertension review articles hypertension PubMed articles hypertension PubMed Central articles hypertension 2023 articles hypertension 2024 articles hypertension Scopus articles hypertension impact factor journals hypertension Scopus journals hypertension PubMed journals hypertension medical journals hypertension free journals hypertension best journals hypertension top journals hypertension free medical journals hypertension famous journals hypertension Google Scholar indexed journals cardiovascular articles cardiovascular Research articles cardiovascular review articles cardiovascular PubMed articles cardiovascular PubMed Central articles cardiovascular 2023 articles cardiovascular 2024 articles cardiovascular Scopus articles cardiovascular impact factor journals cardiovascular Scopus journals cardiovascular PubMed journals cardiovascular medical journals cardiovascular free journals cardiovascular best journals cardiovascular top journals cardiovascular free medical journals cardiovascular famous journals cardiovascular Google Scholar indexed journals cerebrovascular disease  articles cerebrovascular disease  Research articles cerebrovascular disease  review articles cerebrovascular disease  PubMed articles cerebrovascular disease  PubMed Central articles cerebrovascular disease  2023 articles cerebrovascular disease  2024 articles cerebrovascular disease  Scopus articles cerebrovascular disease  impact factor journals cerebrovascular disease  Scopus journals cerebrovascular disease  PubMed journals cerebrovascular disease  medical journals cerebrovascular disease  free journals cerebrovascular disease  best journals cerebrovascular disease  top journals cerebrovascular disease  free medical journals cerebrovascular disease  famous journals cerebrovascular disease  Google Scholar indexed journals

Article Details

1. Introduction

Evidence abounds that there is increasing global prevalence and trends of overweight among people of several nations and this poses a myriad of health consequences, reduced quality of life and poor drug compliance as well as an increased risk of premature illness and death latter in life [1, 2]. Excess adiposity is well documented as one of the principal health threats and is a major risk factor for type 2 diabetes, hypertension, cardiovascular and cerebrovascular disease [3]. The global nature of the obesity epidemic has been formally recognized by the World Health Organization in 1997 [4]. Weight gain is a well documented serious side effect of antipsychotic therapy and many studies have tried to assess the impact of the various types of antipsychotic on the weight of those taking them [5-7]. However, most of these studies were carried out in the developed world. There is a paucity of similar studies in the undeveloped world of which Nigeria is a part. It is also known that there is obvious genetic and racial differences in the cytochrome P450 drug metabolizing enzymes of Caucasians compared to non-Caucasians [8, 9].

In the light of the foregoing, this study aims at evaluating the body mass index changes of patients on antipsychotic therapy in a tertiary hospital in Nigeria. The comparison between the typical and atypical antipsychotics was done. It is expected that results from this study will not only add to our knowledge about the pharmacodynamics of these medications but it will guide clinicians in prescribing them to patients and provide a reliable data which will enable health care policy makers enunciate more patient friendly policies with respect to making available the best medications.

2. Subjects and Method

This prospective cross-sectional study was conducted at the psychiatric clinic of the Madonna University Teaching Hospital over an eight month period, from February 2014–October 2014.

2.1 Instruments

For this study, the instruments used are as follows:-

  1. The Schedule for Clinical Assessment in Neuropsychiatry (SCAN), interview schedule, version 2.1
  2. Socio-demographic questionnaire

The Schedule for Clinical Assessment in Neuropsychiatry (SCAN), interview schedule, version 2.1 is an excellent instrument for diagnosing psychiatric disorders based on the ICD 10 diagnostic criteria [10]. A questionnaire containing socio-demographic variables, prepared by the researchers was administered to each subject.

2.2   Procedure

Before the commencement of the study, approval of the ethical committee of the institution was sought and informed consent obtained from the subjects enlisted into the study. All psychiatric patients placed on antipsychotic treatment for the first time were included in the study while all those who have been on antipsychotics before the commencement of the study were excluded. All psychiatric patients who attended the clinic within the study period and consented to the study were included in the study.

The height and weight of the subjects were recorded before the commencement of treatment with antipsychotics. From this, the baseline Body Mass Index (BMI) was derived. The BMI was calculated by dividing the weight of the patient (in kilograms) by the square of his/her height (in meters). Diagnoses of their conditions were earlier made using SCAN based on the ICD 10 criteria. Each subject was given a one month appointment (for out-patients) and the BMI subsequently repeated (BMI2) as well as for the subsequent two months (BMI3 and BMI4).

2.3   Sample size estimation

Sample size was calculated using the formula of proportions N=Z2pq/E2 [11] where N=minimum sample size. Z=1.96 (standard normal deviation for 95% confidence interval level). P=Proportion of population with condition studied (10%). Q=Complementary probability (100–p)=100–10=90. E=precision required (tolerable sampling error)=5%.

 N=  1.962 x 10 x 90

                   52

=              138.298

The sample size was rounded off to 140.

The data was analyzed using the statistical package for social sciences (SPSS) at 5% level of significance and 95% conference interval.

3. Results

Out of one hundred and forty subjects (140) enlisted, 138 completed it. Table 1 shows the frequencies of the various socio-demographic and clinical variables of the subjects. The greatest percentage of the subjects were schizophrenic (43.5%), aged between 31-40 yrs (52.2%), male (69.6%), unemployed (47.8%), single (47.8%), and had secondary education (39.1%). Ninety (65.2%) of the subjects had the typical antipsychotics (Haloperidol or Chlorpromazine) prescribed for them while 48(34.8%) had the atypical antipsychotics (Risperidone or Olanzapine) prescribed for them.

Variable

n

   %

Diagnosis

 

 

Schizophrenia

60

43.5

Mood Disorder

48

34.5

Anxiety Disorder

6

4.3

Substance use disorder

24

17.4

Age (in Years)

 

 

11 – 20

12

8.7

21 – 30

36

26.1

31 – 40

72

52.2

41 – 50

12

8.7

51 – 60

6

4.3

Gender

 

 

Female

42

30.4

Male

96

69.6

Employment

 

 

Unemployed

66

47.8

Unskilled

30

21.7

Skilled

24

17.4

Professional

18

13

Marital Status

 

 

Single

66

47.8

Separated/Divorced

18

13

Married

36

26.1

Widowed

18

13

Literacy Status

 

 

No formal Education

18

13

Primary Education

42

30.4

Secondary Education

54

39.1

Tertiary Educations

24

17.4

Antipsychotics used

 

 

Haloperidol/Chlorpromazine

90

65.2

Risperiodne / Olanzapine

48

34.8

Table 1: Frequencies of the various sociodemographic and clinical variables.

Table 2 depicts the distribution of the mean values of the body mass index (BMI) of the subjects every month on four different occasions based on the antipsychotics used. Before the administration of antipsychotics, at the commencement of the study, the mean BMI of the subjects (BMI1) was 23.7461 +­ 3.58270. The mean BMI (BMI2) of the subjects after one month of the use of antipsychotics was 25.0074 + 3.99667 (the mean BMI for those on typical antipsychotics was 23.518 + 3.46431 while for those on atypical antipsychotics was 27.8000 + 3.40912).

After 2 months of using antipsychotics, the mean BMI (BMI3) of the subjects was 25.9609 + 4.24540. For those on typical antipsychotic, the mean BMI was 24.3467 + 3.60147 while that of those on atypicals was 28.9875 + 3.69189. After 3 months of taking antipsychotics, the mean BMI (BMI4) of the subjects was 27.1261 + 4.66810. For those on typical antipsychotics, the mean BMI was 25.0800  + 3.76373 while that of atypical antipsychotic users was 30.9625 + 3.69414.

Condition

n

Mean

Standard Deviation

Minimum

Maximum

BMI(1)

(before use of Antipsychotics)

Total

 

 

138

23.7461

3.58270

17.25

 

 

32.90

BMI(2)

Haloperidol/Chlorpromazine

 

90

23.5180

3.46431

17.50

 

28.30

Risperidone/Olanzapine

48

27.8000

3.40912

23.50

34.80

Total

138

25.0074

3.99667

17.50

34.80

BMI (3)

Haloperidol/chlorpromazine

 

90

24.3467

3.60147

17.80

 

29.40

Risperidone/ Olanzapine

48

28.9875

30.69189

25.30

36.70

Total

138

25.9609

4.24540

17.30

36.70

BMI(4)

Haloperidol/Chlorpromazine

 

90

25.0800

3.76373

18.20

 

30.00

Risperidone/ Olanzapine

48

30.9625

3.69414

26.30

38.40

Total

138

27.1261

4.66810

18.20

38.40

Table 2:   Distribution of the mean values of the body mass index (BMI) of the subjects based on the antipsychotic used.

Table 3 shows the table of ANOVA values comparing the mean BMI of the two groups of antipsychotic users. The result shows that there is statistically significant difference between the two groups of antipsychotic users on the three occasions they were compared:

df=1, F=48.354, P=0.000

df=1, F=51.082, P=0.000

df=1, F=77.451, P=0.000

Condition

Sum of Squares

df

F

Significance

BMI(2) between the 2  groups of antipsychotic users 

573.982

1

48.354

0.000 ?

BMI (3)  between the 2 groups of  antipsychotic users 

674.212

1

51.082

0.000 ?

BMI(4) between the 2 groups of antipsychotic users 

1083.250

1

77.451

0.000 ?

      ? significant

Table 3: Table of anova values.

4. Discussion

This study showed that there was a progressive increase in the weight of the subjects on antipsychotics. This is suggested by the raised BMI changes for both typical and atypical antipsychotics from the beginning of the treatment to the end of four months when the fourth BMI was calculated. However the atypical antipsychotics, risperidone and olanzapine caused more increase in BMI compared to the typical antipsychotics, haloperidol and chlorpromazine across board. The table of ANOVA values shows that the differences in BMIs caused by the two antipsychotic types with their use over time were consistently significant. Although many-factors including sedentary lifestyle, unhealthy food habits, genetic susceptibility and antipsychotic treatment are known causes of weight gain, antipsychotic-induced weight gain remains an important concern in the management of patients treated for psychosis [12].

The result of this study with respect to greater penchant for causing weight gain by the atypical antipsychotics compared with the typical antipsychotics is similar to results from previous studies [5, 6, 12]. Madhubhashinee et al reported that most antipsychotics cause weight gain and the risk appears to be higher with olazapine and clozapine [12].

Reports on the socio-demographic characteristics of patients on antipsychotics are conflicting. In this study, a greater percentage of the patients are males and unemployed. This is in agreement with some studies [13, 14]. Nevertheless, these studies also reported that most of the patients on antipsychotics have only primary or basic education contrary to the finding in our study, that a greater percentage of our study cohort had a secondary education. Methodological differences and the fact that the study was carried out in a referral centre (a tertiary hospital) may be explanatory.

5. Conclusion

Weight gain and obesity is a public health problem that is assuming global proportions. Considering the invaluable role antipsychotics play in the treatment of psychiatric patients, non pharmacologic interventions, such as dietary counseling, exercise programme and cognitive as well as behavioural strategies are highly recommended for patients on antipsychotics to help control the undesirable tendency towards weight gain caused by these drugs. A greater majority of our patients were schizophrenics. This is similar to reports from other studies.

6. Authors’ Contributions

Dr Chukwujekwu conceived the paper, oversaw data collection, conducted data analysis, wrote the manuscript and approved final version. Dr Olose participated in data collection and interpretation, critically revised the manuscript and approved final version. The authors declare that they have no conflict of interest.

7. Limitation

The two groups compared were not matched for age and sex. This would have helped eliminate confounding variables to the barest minimum.   

References

  1. Dietz WH. Health Consequences of Obesity In Youth: Childhood Predictors of Adult Disease. Pediatrics 101 (1998): 518-525.
  2. de Onis M, Blossner M. Prevalence and Trends of Overweight Among Pre-school Children In Developing Countries. AMJ Clin Nutr 72 (2000): 1032-1039.
  3. Cabailero B. The Global Epidemic of Obesity: An Overview. Epidemiologic Reviews 29 (2007): 1-5.
  4. World Health Organization. Obesity: Preventing and Managing The Global Epidemic, Report Of A WHO Consultation, 2000. Geneva, Switzerland World Health Organization (WHO technical report series 894). (2000).
  5. Ghate SR, Porucznik CA, Said Q, et al. Association Between Second-Generation Antipsychotics And Change In Body Mass Index In Adolescents. J Adolesc Health 52 (2013): 336-343.
  6. Susilova L, Ceskova E, Hampel D, et al. Changes In BMI In Hospitalized Patients During Treatment With Antipsychotics, Depending On Gender And Other Factors. Int. J. Psychiatry Clin Pract 2 (2017): 112-117.
  7. Correll CU, Lencz T, Malhotra A. Antipsychotic Drugs and Obesity Trends. Mol Med 17 (2011): 97-107.
  8. Yamaori S, Yamazaki H, Iwano S, et al. Ethnic Differences Between Japanese And Caucasians In The Expression Levels of mRNAS for CYP3A4, CYP3A5 and CYP3A7: Lack of Co-Regulation of The Expression OF CYP3A In Japanese Livers. Xenobiotica 35 (2005): 69-83.
  9. Bains RK. African Variation at Cytochrome P450 Genes: Evolutionary Aspects and The Implications For The Treatment Of Infectious Diseases. Evol Med Public health 1 (2013): 118-134.
  10. Schedules for Clinical Assessment in Neuropsychiatry (Version 2.1) Interview. World Health Organization, Assessment, Classification and Epidemiology, Geneva (1999).
  11. Livanga SK, Lemeshow S. Sample Size Determination in Health Studies: A Practical Manual 1991. WHO, Geneva 15 (1991).
  12. Madhubhashinee D, Raveen H, Suhashini, R, et al. Antipsychotic-Associated Weight Gain: Management Strategies And Impact On Treatment Adherence. Neuropsychiatr Dis Treat 13 (2017): 2231-2241.
  13. Monmany JM, Claero IT, Geomez NB, et al. Clinical And Socio-Demographic Characteristics, Of A Sample Of Out-Patients With Long Acting Injectable Antipsychotics Treatment. European Psychiatry 33 (2016): 543.
  14. Sau L, Bernado M, Gomez A, et al. Socio-Demographic clinical and treatment characteristics of relapsing schizophrenic patients. Nord J Psychiatr 67 (2013): 22-29.

© 2016-2024, Copyrights Fortune Journals. All Rights Reserved