|Year : 2019 | Volume
| Issue : 1 | Page : 77-81
Screening for mild cognitive impairment among noncommunicable disease patients attending a rural primary health center in Puducherry, South India
Yuvaraj Krishnamoorthy, Gokul Sarveswaran, Manikandanesan Sakthivel, Tanveer Rehman, Marie Gilbert Majella, S Ganesh Kumar
Department of Preventive and Social Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
|Date of Web Publication||4-Feb-2019|
Department of Preventive and Social Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry - 605 008
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Cognitive impairment among noncommunicable disease (NCD) patients causes significant burden to the patients and families by increasing the dependency level and risk of developing Alzheimer's disease in the future. Hence, the current study was done to screen for mild cognitive impairment among NCD patients attending rural primary health center in Puducherry. Materials and Methods: A facility-based cross-sectional study was done among 260 NCD patients attending rural health center of tertiary care center in Puducherry from February to March 2018. Information regarding sociodemographic and behavioral characteristics was done using semi-structured questionnaire, and cognitive function was screened using mini-mental status examination tool. Results: Among the 260 participants, majority were females (66.2%) and belonged to elderly age group (42.7%). About 44% of the participants did not have any formal education and almost three-fourths (70%) were unemployed. The most common NCD was hypertension (71.2%), followed by diabetes (56.2%) and bronchial asthma (15%). Proportion of cognitive impairment was 10.8% (95% confidence interval: 7.4–15.0). Cognitive impairment was three times more prevalent among elderly participants (prevalence ratio [PR] – 3.35, P = 0.002) when compared to the age group of <60 years. Similarly, the proportion of participants with cognitive impairment was twice among uneducated (PR – 2.34, P = 0.02) compared to the literate participants. Conclusion: The current study found that one in ten NCD patients has mild cognitive impairment. The elderly and illiterates were found to have more risk of cognitive dysfunction. Hence, opportunistic screening for cognitive dysfunction needs to be done at the primary health-care level.
Keywords: Cognition, mental health, noncommunicable diseases
|How to cite this article:|
Krishnamoorthy Y, Sarveswaran G, Sakthivel M, Rehman T, Majella MG, Kumar S G. Screening for mild cognitive impairment among noncommunicable disease patients attending a rural primary health center in Puducherry, South India. J Nat Sc Biol Med 2019;10:77-81
|How to cite this URL:|
Krishnamoorthy Y, Sarveswaran G, Sakthivel M, Rehman T, Majella MG, Kumar S G. Screening for mild cognitive impairment among noncommunicable disease patients attending a rural primary health center in Puducherry, South India. J Nat Sc Biol Med [serial online] 2019 [cited 2019 Aug 24];10:77-81. Available from: http://www.jnsbm.org/text.asp?2019/10/1/77/251511
| Introduction|| |
Noncommunicable diseases (NCDs), especially cardiovascular diseases and diabetes mellitus (DM), are the leading cause of mortality worldwide. Morbidity, mortality, and disability attributable to the major NCDs account for almost 60% of all deaths and 47% of the global burden of disease. Elderly population with NCDs have greater risk of developing several complications including neurological complications such as dementia.
Studies across the world have shown the association between NCDs and accelerated decline of cognitive function leading to mild cognitive impairment.,, However, the causal pathway of relation between NCDs and cognitive impairment is unknown. Mild cognitive impairment is the transitional phase between the normal aging process and dementia. Cognitive impairment causes significant burden to the patients as well as to their families. For the patients, it increases the dependency level and risk of developing Alzheimer's disease in the future, whereas for the families, there will be significant economic and social burden such as financial hardships and social isolation. With increase in life expectancy, the burden of cognitive impairment is also bound to increase across the countries (both developed and developing countries).
India is in a unique situation because of its rapid epidemiological transition leading to increase in elderly population and higher prevalence of NCDs, such as diabetes and cardiovascular diseases. Similar situation is happening in other developing nations too. Studies conducted in India showed prevalence of cognitive impairment to be around 4.6% and significant association between cognitive impairment and NCDs.,
Hence, screening for cognitive decline among NCD patients will lead to early identification of undiagnosed dementia. Consequently, the patients and their families will seek health care at the earliest to avert the complications and the appreciable adversities. Screening can be done at the primary health-care level itself to cover the majority of the population and determine the magnitude of the condition. This will also help in following up of NCD patients and monitoring their performance over the time as they have frequent contacts with health-care workers in the clinic.
Even though many studies have been conducted regarding the prevalence of cognitive impairment among elderly population throughout the Indian population, there was only limited literature available regarding the prevalence of cognitive impairment among NCD patients. Thus, the current study was done to screen for mild cognitive impairment among NCD patients attending rural primary health center in Puducherry, South India.
| Materials and Methods|| |
Study design and study setting
A facility-based cross-sectional study was conducted among the patients attending NCD clinic of Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER) Rural Health Center (JIRHC) from February to March 2018. JIRHC caters to a population of around 10,000 spread over four villages, namely, Ramanathapuram, Thondamanatham, Pillaiyarkuppam, and Thuthipet. All the four villages are located within 4 km of the health center, which is located in Ramanathapuram village. Senior Resident from the Department of Preventive and Social Medicine, JIPMER, is the Medical Officer (MO) in charge. In providing the health-care services of a primary health center, the MO is assisted by the postgraduate doctors and undergraduate intern trainees, posted from the Department of Preventive and Social Medicine, JIPMER, as well as by the nursing staff and public health nurses.
NCD clinic of JIRHC is a special clinic established exclusively for the management of NCDs: predominantly DM and hypertension; others being bronchial asthma, stroke, and epilepsy. It is conducted every Wednesday in Ramanathapuram health center and on alternate Tuesdays in Thondamanatham subcenter, under JIRHC. On an average, around 60 DM patients attend each NCD clinic and avail the health-care services. All the adult patients attending the NCD clinic during the study period were included in the study. Patients who were visually challenged were excluded from the study as the current study requires visual interpretation for cognitive assessment.
Sample size and sampling technique
Sample size was calculated by OpenEpi software (v 3.01 updated on 2013, USA) using prevalence of cognitive impairment among the chronic disease patients as 33.7% based on a previous study; with absolute precision of 6% and a confidence interval (CI) of 95%, minimum sample size required for the study was 197. However, all the patients satisfying the inclusion criteria were included in the study. Convenience sampling technique was applied to recruit the participants into the study.
Study procedure and study tool
Three training doctors posted in JIRHC were chosen as data collectors. They were sensitized regarding the objectives of the study, confidentiality of information, participants' rights, and informed consent and were also trained to administer the questionnaire to the individuals. Postgraduates posted in the center supervised the data collection procedure by reviewing all the questionnaires at the end of each day to ensure completion of data collection forms and addressed any issues faced by the data collectors.
The purpose and procedures involved in the study were explained to the participants before administration of the questionnaire. They were also assured regarding confidentiality of the information, and data collection was started after obtaining informed consent. The questionnaire had three sections. The first section consisted of sociodemographic characteristics. The second comprised questions related to behavioral characteristics such as current tobacco and alcohol use and adequacy of physical activity. Current tobacco users were participants who must have used tobacco at least once in the past 1 month before the study period. Current alcohol users were participants who must have consumed alcohol in any amount in the past 1 year. One hundred and fifty minutes of moderate intensity physical activity or 75 min of vigorous intensity physical activity per week was considered to have adequate physical activity. The final part had the mini-mental status examination (MMSE) tool to determine the mild cognitive impairment among study participants.
MMSE is a short, easily administered 11-item scale which screens for cognitive function. The Cronbach's alpha reliability of the questionnaire was reported to be 0.82. MMSE had been standardized for our research purpose by forward translation to Tamil and rechecked by expert panel back translation to English. After pretesting and cognitive interviewing, the final version was prepared. Based on the scores obtained, they were classified into normal (score 25–30) and mild cognitive impairment (score <25). Each test took about 5–10 min.
Data were entered in EpiData v 3.01 software (manufactured by EpiData association on the year 1999 in Denmark), and analysis was done using SPSS version 19.0 (IBM, Armonk, NY, United States of America). Continuous variables were summarized as mean (standard deviation). Proportion of mild cognitive impairment was summarized as percentages with 95% CI. Bivariate analysis (Chi-square test/Fisher's exact test) was used to find the association between sociodemographic factors, behavioral factors, and mild cognitive impairment. Predictors of mild cognitive impairment (independent effects) were identified using multivariable analysis (log-binomial regression), considering mild cognitive impairment as dependent variable and age category, gender, education, occupation, tobacco use, alcohol use, and physical activity as explanatory variables (variables with P value up to 0.20 were considered into the multivariate regression model). Unadjusted prevalence ratio (PR) and adjusted PR (aPR) ratio with 95% CI were calculated. P < 0.05 was considered statistically significant.
| Results|| |
A total of 277 patients attended the NCD clinic during our study period; out of which, 260 (93.8% response rate) were included in the study. Seventeen patients were not included in the study as they did not give consent to participate in the study.
Sociodemographic characteristics of the study participants were described in [Table 1]. Majority of the study participants were females (66.2%) and belonged to elderly age group (42.7%). Nearly 44% of the participants did not have any formal education and almost three-fourths (70%) were unemployed. More than half of them (56.5%) belonged to nuclear family. The most common NCD was hypertension (71.2%), followed by diabetes (56.2%) and bronchial asthma (15%). Mean duration of hypertension and diabetes among the study participants was found to be 6 years and 5 years, respectively.
[Table 2] shows the behavioral characteristics among the study participants. Less than 10% of the study participants were current tobacco users; 28 (10.8%) of the participants were current alcohol users; more than half of the participants (60%) were not physically active.
|Table 2: Behavioral characteristics of the patients attending noncommunicable disease clinic in a primary health-care center in rural Puducherry (n=260)|
Click here to view
Proportion of cognitive impairment among the study participants was 10.8% (95% CI: 7.4–15.0). Cognitive impairment was more common among bronchial asthma patients as 15.4% of asthma patients had mild cognitive impairment. This was followed by hypertension (11.9%) and DM (11.6%). [Table 3] shows the association of sociodemographic variables with cognitive impairment. It was found that the cognitive impairment was three times more prevalent among elderly participants (60 years or more) (PR –3.35, P = 0.002) when compared to the age group of < 60 years. Similarly, proportion of participants with cognitive impairment was twice among uneducated (PR –2.34, P = 0.02) compared to the literate participants. Proportion of cognitive impairment was also found to be significantly more among tobacco users (PR – 6.01, P = 0.001) and alcohol users (PR –2.76, P = 0.009), respectively. Gender, occupation, family type, and physical activity were not associated with cognitive impairment.
|Table 3: Factors associated with cognitive impairment among patients attending noncommunicable disease clinic in a primary health-care center in rural Puducherry (n=260)|
Click here to view
Predictors of mild cognitive impairment among the study participants were described in [Table 4]. Elderly age group (aPR –2.64, P = 0.02), female gender (aPR –3.21, P = 0.01), and tobacco (aPR – 5.90, P = 0.001) and alcohol use (aPR –1.73, P = 0.001) were found to be the significant predictors of mild cognitive impairment among NCD patients.
|Table 4: Predictors of cognitive impairment among noncommunicable disease patients in rural Puducherry (n=260)|
Click here to view
| Discussion|| |
This was a facility-based cross-sectional study conducted among NCD patients attending a primary health center in rural Puducherry to screen for mild cognitive impairment. Proportion of mild cognitive impairment among the study participants was 10.8%. The study found elderly age group, females, and tobacco and alcohol users as significant predictors of mild cognitive impairment.
Large-scale population study in India showed prevalence of mild cognitive impairment to be around 4.6%. Studies around India among elderly population showed prevalence of cognitive impairment ranging from 3.5% to 7.78%., The current study reported the prevalence to be 10.8%, which was clearly in excess of general and elderly population. However, this can also be due to the facility-based design and sampling technique involved in the current study. Hence, further community-based research with probability-based sampling technique can be done to find whether the proportion of cognitive impairment among NCD patients is in excess when compared to general population.
Studies around the world assessing the prevalence of cognitive impairment among NCD patients such as diabetes and hypertension showed varying proportion ranging from 1.7% to 40%.,, A study done among diabetes patients in India also reported higher prevalence 33.7%, which is contrast to the current study finding. However, the current study found that only 11.6% of diabetes patients had mild cognitive impairment. This can be attributed to the duration of the disease suffered by the patients, which was lower in the current study when compared the above-mentioned study. In addition, sample size was not separately calculated for individual NCDs, which might have underestimated the prevalence in diabetes patients.
However, a study done among hypertension patients in India showed similar finding when compared to the current study. Large population-based study in Ballabgarh, India, has found that around 13% of hypertensive patients have cognitive impairment which was comparable to the proportion (12%) found in our study. Hence, further longitudinal research can be done targeting the hypertensive patients to find the possible factors involved and develop appropriate strategies to tackle them.
The elderly, females, and tobacco and alcohol users were found to be the predictor for cognitive impairment among NCD patients in the current study. Similar findings were found in most of the studies conducted around the world as well as in India.,,, A study in Punjab and Delhi among NCD patients also reported elderly age group, female gender, physical activity, and tobacco and alcohol use as determinants for cognitive impairment., Hence, it is important to counsel the NCD patients about the lifestyle modifications such as engaging in physical activity and avoidance of tobacco and alcohol use which will help in improving their disease status as well as cognitive function.
Major strength of the study was the assessment of cognitive impairment among the different NCDs. Most of the available literature reported data of cognitive impairment among diabetes or hypertension patients alone. Higher response rate (93.8%) and use of validated scale add to the strength of the study.
However, the study had certain limitations. Since the study conducted was facility-based which is covering smaller geographical region, the results might not be representative of the general population and impede generalizability. This was conducted as a cross-sectional study, and hence, causal association between the sociodemographic and behavioral characteristics and cognitive impairment cannot be inferred.
Cognitive impairment needs to be screened which will help in predicting the development of dementia in the future, especially among NCD patients. Several evidences around the world show association of cognitive impairment with diabetes and hypertension.,, Although diagnosis can be done in secondary or tertiary care setting, screening and appropriate referral services can be done at primary health-care level itself. Training of health workers needs to be done to carry out the screening activities.
The findings of this study will help policymakers to formulate strategies for an inclusive engagement of primary care providers to identify and refer the cases of cognitive impairment among NCD patients at the earliest. Further longitudinal research of large scale needs to be conducted to find various predictive factors associated with cognitive impairment.
| Conclusion|| |
The current study found that one in ten NCD patients have mild cognitive impairment. The elderly, females, and tobacco and alcohol users were found to be significant predictors of cognitive impairment. Hence, such target groups need to be identified and screened for cognitive impairment during the point of contact with health-care provider at primary level itself. Appropriate referral of suspected patients should be done for further evaluation which will help in achieving earlier diagnosis and prevent the development of complications.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Das SK, Pal S, Ghosal MK. Dementia: Indian scenario. Neurol India 2012;60:618-24.
] [Full text]
Khullar S, Kaur G, Dhillon H, Sharma R, Mehta K, Singh M, et al
. The prevalence and predictors of cognitive impairment in type 2 diabetic population of Punjab, India. J Soc Health Diabetes 2017;5:47-53. [Full text]
Lindsay AZ, Krish C, Justin YK, James WR. Diabetes and cognitive impairment. Curr Diab Rep 2016;16:87.
Kataria L, Pandya H, Shah S, Shah H, Gerg R. Prevalence and pattern of cognitive dysfunction in type 2 diabetes mellitus. Int J Med Appl Sci 2013;2:246-52.
Gondim AS, Coelho Filho JM, Cavalcanti AA, Roriz Filho JS, Nogueira CB, Peixoto Junior AA, et al.
Prevalence of functional cognitive impairment and associated factors in Brazilian community-dwelling older adults. Dement Neuropsychol 2017;11:32-9.
Sosa AL, Albanese E, Stephan BC, Dewey M, Acosta D, Ferri CP, et al.
Prevalence, distribution, and impact of mild cognitive impairment in Latin America, China, and India: A 10/66 population-based study. PLoS Med 2012;9:e1001170.
Sharma D, Mazta SR, Parashar A. Prevalence of cognitive impairment and related factors among elderly: A population based study. J NTR Univ Health Sci 2013;2:171-6. [Full text]
Das SK, Banerjee TK, Mukherjee CS, Bose P, Biswas A, Hazra A, et al
. An urban community based study of cognitive function among non-demented elderly population in India. Neurol Asia 2006;6:37-48.
Lazo-Porras M, Ortiz-Soriano V, Moscoso-Porras M, Runzer-Colmenares FM, Málaga G, Jaime Miranda J, et al.
Cognitive impairment and hypertension in older adults living in extreme poverty: A cross-sectional study in Peru. BMC Geriatr 2017;17:250.
Gorska-Ciebiada M, Saryusz-Wolska M, Ciebiada M, Loba J. Mild cognitive impairment and depressive symptoms in elderly patients with diabetes: Prevalence, risk factors, and comorbidity. J Diabetes Res 2014;2014:179648.
Eze C, Basil E, Uma A, Ikenna O. The prevalence of cognitive impairment amongst type 2 diabetes mellitus patients at Abakaliki South-East Nigeria. J Metab Syndr 2015;4:171.
Pandav R, Dodge HH, DeKosky ST, Ganguli M. Blood pressure and cognitive impairment in India and the United States: A cross-national epidemiological study. Arch Neurol 2003;60:1123-8.
[Table 1], [Table 2], [Table 3], [Table 4]