|Year : 2022 | Volume
| Issue : 1 | Page : 50-55
Multiplicity of noncommunicable diseases among the elderly in a suburban area of Delhi
Tushar Prabhakar, Manish Kumar Goel, Anita Shankar Acharya
Department of Community Medicine, Lady Hardinge Medical College, New Delhi, India
|Date of Submission||02-Oct-2021|
|Date of Acceptance||24-Dec-2021|
|Date of Web Publication||30-Jun-2022|
Department of Community Medicine, Lady Hardinge Medical College, New Delhi
Source of Support: None, Conflict of Interest: None
Introduction: Continuing advancements in quality of health care has led to increased life expectancy over time. This in turn has resulted in increased prevalence of noncommunicable diseases (NCDs), especially among the elderly. An appropriate portrayal of its epidemiology is essential to adequately understand the health-care needs of the population. The evidence generated from the study will give us an incentive to address the rising burden of polymorbidities. We did the study to assess the prevalence and pattern of NCDs in the elderly above 60 years of age and to determine age- and sex-wise distribution of single and multiple NCDs.
Materials and Methods: A community-based cross-sectional study was conducted among 350 elderly participants over 60 years of age in Mehrauli area of Delhi. Data were collected using a semi-structured questionnaire. Detailed general and systemic examination was also done.
Results: A total of 87.4% of the study population were suffering from at least one NCD. The number of NCDs per person is 2.41. Overall, 80 out of the total 350 study participants (22.9%) had a single NCD, whereas 226 (64.6%) had two or more NCDs. Hypertension was the most prevalent NCD, followed by cataract, osteoarthritis, diabetes mellitus, and obesity.
Conclusion: The prevalence of NCDs was quite high among the elderly. Multimorbidity was more common among the oldest-old age group and elderly women. This calls for increased focus on timely and comprehensive screening for NCDs in adults and asserts the need to approach the screening and management of NCDs in a more holistic way and not as isolated health events.
Keywords: Elderly, India, multimorbidity, noncommunicable diseases
|How to cite this article:|
Prabhakar T, Goel MK, Acharya AS. Multiplicity of noncommunicable diseases among the elderly in a suburban area of Delhi. Indian J Community Fam Med 2022;8:50-5
|How to cite this URL:|
Prabhakar T, Goel MK, Acharya AS. Multiplicity of noncommunicable diseases among the elderly in a suburban area of Delhi. Indian J Community Fam Med [serial online] 2022 [cited 2022 Nov 27];8:50-5. Available from: https://www.ijcfm.org/text.asp?2022/8/1/50/349389
| Introduction|| |
Aging is a natural process, associated with physical, physiological, and cognitive decline. Globally, the population of older persons is growing at a rate of 2.6%/year, considerably faster than the population as a whole which is increasing at 1.1% annually.
The proportion of elderly in India and their rise in subsequent years is likely to follow a similar trend. India is in a phase of demographic transition wherein the elderly population, currently constituting 138 million (10.1% of the total population), has shown a sustained rise from 103 million (8.6% of the total population) in 2011 and a 35.8% increase in proportion of elderly as compared to 12.4% in general population and is projected to reach 194 million (13.1%) by 2031.
The increasing elderly population is posing its own challenges, of which one of the major challenges is having multiple chronic diseases. Polymorbidity or multimorbidity can be defined as “existence of multiple medical conditions in a single individual.” Some have tried to define it as an accumulation of two or more chronic diseases, whereas others have considered it to be the accumulation of three or more diseases.,
The problem of multiple noncommunicable diseases (NCDs) among Indian older adults is relatively underexplored primarily owing to the lack of nationally representative data on chronic diseases and associated factors. Furthermore, studies in the past have focused on multimorbidity as counts of conditions rather than specific combination of conditions.
This study aims to assess the prevalence and pattern of selected NCDs in the geriatric age group, determine the age- and sex-wise distribution of single and multiple morbidities, and identify the common combination of NCDs.
| Material and Methods|| |
A community-based observational cross-sectional study was conducted among study participants in Mehrauli area of Delhi which is one of the field practice areas of a government medical college of Delhi.
The study was done among the elderly population over 60 years of age who had been residing in the study area for at least a year and were willing to participate. The study area has a mixed population with families belonging to all socioeconomic strata with people of local ancestry as well as migrant population coexisting homogenously. Those who were seriously moribund or bedridden or were unable to respond to the interview due to physically limiting disabilities were excluded.
The sample size was calculated using N = Z2 P q/l2. Taking 64%, as prevalence of NCDs, the sample size calculated for 95% level of significance, 10% allowable error, and design effect = 1.5 was found to be 337 participants that was rounded off to 350. Three out of eight wards of Mehrauli area were selected randomly and subsequently systematic random sampling was done. The collective approximate population of the selected wards was found to be around 34,000. Sampling frame that included the elderly >60 years was assessed using national population percentage of elderly (8.6% of total population). It was found that every eighth house needed to be visited in order to fulfill the sample size. The first house was decided by selecting a random number between 1 and 10 using lottery method. In case there were two or more elderly in a household, only one was randomly selected for the study. In case there was no elderly person in a household, the next house was selected. In case a house was found locked even after three consecutive visits, the next house was selected. Whenever a crossroad came up, the road to the left was taken. The interview and examination was conducted by the first author and the average time taken for it was around 30 min. The data collection was done from January to December 2019. Permission for conducting the study was taken from the Ethics Committee for Human Research, LHMC, New Delhi. Written informed consent was taken from the study subjects in the language they understood, and confidentiality of the subjects was maintained.
A self-designed, pretested, semi-structured interview schedule and screening questionnaire was used for data collection regarding sociodemographic particulars and selected NCDs (diabetes mellitus, hypertension, osteoarthritis, senile cataract, and obesity) on the latest documented investigation reports. Apart from this, information regarding other known NCDs that were diagnosed previously on the basis of medical records by a health practitioner was also taken. It was followed with detailed general and systemic examination. Laboratory investigation included measurement of blood sugar using glucometer. Operational definitions used for diagnosing new cases were as follows:
According to WHO, Type 2 Diabetes mellitus is diagnosed in asymptomatic patients if the fasting plasma glucose value is ≥126 mg/dl or if the casual plasma glucose value is ≥200 mg/dl. Symptomatic patients were those having increased frequency of urination, thirst, and/or hunger. First random blood glucose of the participants was measured. In case random blood sugar (RBS) ≤200 mg/dl, the individual was classified as normoglycemic. If RBS ≥200 mg/dl and symptoms were present, diagnosis of diabetes mellitus was confirmed. If RBS ≥200 mg/dl and symptoms were not present, fasting blood glucose was measured the next day to confirm the diagnosis. If FBS ≥126 mg/dl, diagnosis of diabetes mellitus was confirmed.
According to JNC 8 Blood Pressure Guideline, in people above 60 years, pharmacological therapy should be started at a BP of ≥150/90 mmHg. In diabetic population aged 18 years or older, the target blood pressure is <140/90 mmHg. Average blood pressure higher than the aforementioned cutoffs was considered to diagnose hypertension. Blood pressure was recorded in the left arm with the subject in a sitting position. A digital sphygmomanometer was used to take two readings at an interval of 5 min. In case the difference in values was 10 mmHg or more, a third reading was taken and the average of the three was considered the final value.
By measuring body mass index (BMI), participants were categorized as underweight (<18.5 kg/m2), normal or lean (18.5–22.9 kg/m2), overweight (23.0–24.9 kg/m2), and obese (≥25 kg/m2) based on the revised consensus guidelines for India.
History of any significant pain and restriction in movement of large joints was used to diagnose osteoarthritis. Severity was assessed using WOMAC and KATZ tool.
Torch Light examination was used to assess the presence of senile cataract. Grayish-to-white discoloration of lens with or without iris shadow was considered positive for senile cataract.
Data collected from pro forma were coded and entered in IBM. SPSS statistics for Windows. Version 25.0. Armonk, NY: IBM; 2017. All quantitative variables were analyzed in terms of mean and standard deviation, whereas qualitative variables were analyzed through proportions. Student's t-test was used to determine a significant difference in average number of NCDs across gender and various age groups.
| Results|| |
A total of 350 elderly above 60 years were enrolled in the study, of whom 191 (54.6%) were women and 159 (45.4%) were men [Table 1]. The mean age of the study participants was 68.26 ± 6.45 years (range: 60–86 years). Almost two-thirds (66%) of the study group belonged to youngest-old (60–69 years) age group. More than two-thirds (69%) were currently married; the remaining were widowed. More than one-third (33%) of the participants had no formal education, whereas 115 (32.9%) had completed at least high school. More than half (53%) of the study participants belonged to upper middle (52.9%) or upper (0.9%) class as per the Modified Kuppuswamy Scale with Consumer Price Index for Industrial Workers 2019. Majority of the study participants (71%) were living in joint families, whereas 2.9% were living by themselves.
|Table 1: Gender-wise distribution of sociodemographic variables among study participants (N=350)|
Click here to view
A total of 306 (87.4%) of the study population, were suffering from at least one NCD [Table 2]. More than two-thirds (68%) of the study participants were having an already known NCD (s), whereas almost one-fifth (19.4%), though having an NCD, were not aware of it. The proportion of study participants having hypertension was 58% (n = 203), whereas 173 (49.4%) suffered from senile cataract; 115 (32.9%) had osteoarthritis, 106 (30.3%) had diabetes mellitus, and 96 (26.9%) had obesity [Table 3]. It was seen that 238 study participants with known NCDs had a total of 428 NCDs, i.e., 1.79 NCDs per patient. At the end of the study, it was found that the 306 participants had a total of 736 NCDs, that is, 2.41 NCDs per patient. Of these, the 238 participants with previously known NCDs were found to have 634 NCDs. Among them, 136 male participants had 263 NCDs (1.93 NCDs per patient), whereas 170 female participants had 473 NCDs (2.78 NCDs per patient). The ratio of NCDs to patients was highest in the oldest-old age group (3.32), whereas it was 2.68 in the oldest-old age group and 2.14 in the youngest-old age group.
|Table 2: Prevalence of common noncommunicable diseases among study participants (N=350)|
Click here to view
|Table 3: Overall single and multiple noncommunicable diseases among study participants (N=350)|
Click here to view
The average number of NCDs in the total study group was significantly higher at the end of the study [Table 4] across all age and sex groupings.
|Table 4: Age- and sex-wise noncommunicable diseases among total study participants (N=350)|
Click here to view
Overall, 226 (64%) study participants had two or more NCDs [Figure 1], whereas less than a quarter of the total study participants had a single morbidity (n = 80 [22.8%]). Hypertension was the most common NCD in those having a single NCD (n = 38 [47%]) while being followed by cataract (n = 14 [18%]), diabetes mellitus (n = 10 [12%]), osteoarthritis (n = 7 [9%]), obesity (n = 4 [5%]), and asthma (n = 3 [4%]). Hypertension and diabetes mellitus together were present in 64 (18.3%) of the study population, whereas the combination of hypertension, diabetes mellitus, and obesity was seen in 33 (9.4%) of them.
|Figure 1: Pie charts showing the prevalence of single and multiple noncommunicable diseases|
Click here to view
| Discussion|| |
The study was conducted to determine the prevalence of various common NCDs in the elderly population and analyze the existence of multiple NCDs among them.
Seven out of eight individuals, i.e., 87% of participants in our study, were having an NCD. The prevalence of common NCDs varied from 14.1% (Hegde et al.) to 98.2% (Warbhe) among studies conducted by other researchers in the past. However, studies from metro cities showed a similar prevalence of NCDs among the elderly – 87% in Chandigarh by Kaur et al. and 84% in Shimla by Sharma et al. This would be reflective of urbanization and its subsequent lifestyle changes, increasing the risk factor for NCDs.
The total proportion of women having at least one NCD (89.0%) was slightly higher than men (85.5%). Longer life expectancy resulting in increased probability of getting a chronic disease could be a reason for the higher proportion among women.
Multiple NCDs were found in 64.6% of the study participants. This was higher than what was found by Mini and Thankappan in a study that evaluated multimorbidity among the elderly from seven states of India (Kerala, Tamil Nadu, Punjab, Himachal Pradesh, Maharashtra, Orissa, and West Bengal) and reported a prevalence rate of 30.7% among 9852 elderly. A review by de Melo et al. reported that the prevalence of multimorbidity among the elderly from seven studies varied from 30.7% to 57%.
It was observed that the average number of illness per patient was 2.41. This was comparable to the findings by Niranjan and Vasundhra (2.42) among the elderly population of Bangalore, India. Purty et al. found that the average morbidity per person was 2.77, whereas Joshi et al. found it to be 6.9 per person. A possible reason for these higher figures could be a relatively more comprehensive NCD assessment resulting in identification of a high number of previously undiagnosed NCDs.
The number of NCDs per patient increased as age progressed, and for each age group, it was higher among women. The age and gender differences of NCDs were statistically significant. Similar results were observed by Talukdar and Joshi et al.
Among the elderly with polymorbidity, the most common clusters of conditions were hypertension with diabetes, hypertension with osteoarthritis, and osteoarthritis with cataract. Similar findings were found by Mini and Thankappan. Hypertension was the most common monomorbidity as well followed by cataract, diabetes, and osteoarthritis. Close to one in five people in our study (n = 64 [18.3%]) had both diabetes mellitus and hypertension, whereas every tenth individual (n = 33 [9.4%]) had a triad of diabetes mellitus, hypertension, and obesity. This exponentially increases the risk of getting cardiovascular diseases and stroke in future. The findings in our study were higher as compared to Kapil et al. who conducted the study in Nainital where 8.6% of the study participants had both diabetes mellitus and hypertension.
| Conclusion and Recommendations|| |
The study found that the prevalence of NCD among the elderly was notably high and the majority among them had multiple NCD.
This emphasizes the importance of taking a holistic approach toward screening and management of NCDs. Patients suffering from a particular NCD should be routinely screened for other NCDs as well. Usually, multiple guidelines exist for the management of different chronic ailments and most of these guidelines focus on single morbidity. For the elderly who are frail and have cognitive impairment, independent management of NCDs can result in polypharmacy that in turn can lead to high chances of drug–drug interactions in the form of reduction in efficacy or accumulation of side effects.
There is a clear need for greater examination and understanding of the causal mechanisms that underlie multimorbidity toward supporting the development of cost-effective interventions. In addition, these results reiterate the need for preventive health care to move beyond targeting single diseases in favor of directing efforts toward reducing overall morbidity among this population.
Multimorbidity among the elderly often results in increased number of hospital visits, polypharmacy of medications, increased treatment costs, and aggravated burden on the families. It is thus important to identify types of NCDs that have similar environmental and host determinants to better understand the causal mechanisms and onus should be to focus on cost-effective preventive health interventions that have an umbrella effect on such diseases.
The exact prevalence of some relatively common NCDs such as hypothyroidism, asthma, and chronic obstructive pulmonary disease could not be assessed due to diagnostic constraints.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Wongboonsin P, Wongboonsin K, Demographic Dividend and the Future of Asia. In: Ochiai E, Hosoya LA, editors. Transformation of the Intimate and the Public in Asian Modernity. 1st
ed. Leiden: Brill; 2014. p. 91-115.
de Melo LA, Braga LC, Leite FP, Bittar BF, Oseas JM, Lima KC. Factors associated with multimorbidity in the elderly: An integrative literature review. Rev Bras Geriatr Gerontol 2019;22:E180154.
Nguyen H, Manolova G, Daskalopoulou C, Vitoratou S, Prince M, Prina AM. Prevalence of multimorbidity in community settings: A systematic review and meta-analysis of observational studies. J Comorb 2019;9:2235042X19870934. doi: 10.1177/2235042X19870934.
Bhat S, Kumar S. Study on health care seeking behaviour among elderly in rural area. Int J Med Sci Public Health 2017;6:350-2.
Kumar D, Kumari R, Shankar H. Health status and health seeking behaviour of rural geriatric population of Varanasi District, India. Int J Med Sci Public Health 2015;4:1711-4.
World Health Organization. Screening for type 2 diabetes. In: Report of a World Health Organization and International Diabetes Federation Meeting. Geneva: World Health Organization; 2003. Available from: http://www.who.int/iris/handle/10665/68614
. [Last accessed on 2020 Jun 20].
James PA, Oparil S, Carter BL, Cushman WC, Dennison-Himmelfarb C, Handler J, et al.
2014 evidence-based guideline for the management of high blood pressure in adults: Report from the panel members appointed to the Eighth Joint National Committee (JNC 8). JAMA 2014;311:507-20.
Misra A, Chowbey P, Makkar BM, Vikram NK, Wasir JS, Chadha D, et al.
Consensus statement for diagnosis of obesity, abdominal obesity and the metabolic syndrome for Asian Indians and recommendations for physical activity, medical and surgical management. J Assoc Physicians India 2009;57:163-70.
Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of illness in the aged. the index of ADL: A standardized measure of biological and psychosocial function. Jama 1963;185:914-9.
Hegde SK, Agrawal T, Farah F, Amar DS. Factors associated with health seeking behaviour regarding non-communicable diseases among elderly in a rural community in Karnataka (India). Indian J Gerontol 2015;29:283-93.
Warbhe PA, Warbhe R. Morbidity profile, health seeking behaviour and home environment survey for adaptive measures in geriatric population – Urban community study. Int J Med Res Health Sci 2015;4:778-82.
Kaur G, Bansal R, Anand T, Kumar A, Singh J. Morbidity profile of noncommunicable diseases among elderly in a city in North India. Clin Epidemiol Glob Health 2019;7:29-34.
Sharma D, Mazta SR, Parashar A. Morbidity pattern and health-seeking behavior of aged population residing in Shimla hills of north India: A cross-sectional study. J Family Med Prim Care 2013;2:188-93.
] [Full text]
Mini GK, Thankappan KR. Pattern, correlates and implications of non-communicable disease multimorbidity among older adults in selected Indian states: A cross-sectional study. BMJ Open 2017;7:e013529.
Niranjan GV, Vasundhra MK. A study of health status of aged persons in slums of urban field practice area, Bangalore. Indian J Com Med 1996;21:1-4.
Purty AJ, Bazroy J, Kar M, Vasudevan K, Zacharia P, Panda P. Morbidity pattern among the elderly population in the rural area of Tamil Nadu, India. Turk J Med Sci 2006;36:45-50.
Joshi K, Kumar R, Avasthi A. Morbidity profile and its relationship with disability and psychological distress among elderly people in Northern India. Int J Epidemiol 2003;32:978-87.
Talukdar HB. Prevalence of Multimorbidity (Chronic NCDS) and Associated Determinants among Elderly in India. Demography India; 2017. p. 69-76.
Kapil U, Khandelwal R, Ramakrishnan L, Khenduja P, Gupta A, Pandey RM, et al.
Prevalence of hypertension, diabetes, and associated risk factors among geriatric population living in a high-altitude region of rural Uttarakhand, India. J Family Med Prim Care 2018;7:1527-36.
] [Full text]
[Table 1], [Table 2], [Table 3], [Table 4]