Nigerian Postgraduate Medical Journal

ORIGINAL ARTICLE
Year
: 2021  |  Volume : 28  |  Issue : 3  |  Page : 160--168

Nutritional status and morbidity patterns of the elderly in a Northwestern Nigerian hospital: A cross-sectional study


Abdulgafar Lekan Olawumi1, Bukar Alhaji Grema1, Abdullahi Kabir Suleiman1, Yakubu Sule Omeiza2, Godpower Chinedu Michael1, Abdulrahman Shuaibu3,  
1 Department of Family Medicine, Aminu Kano Teaching Hospital, Kano, Nigeria
2 Department of Clinical Services and Training, National Orthopedic Hospital, Kano, Nigeria
3 Office of the Executive Secretary, Primary Healthcare Development Agency, Gombe State, Nigeria

Correspondence Address:
Dr. Abdulgafar Lekan Olawumi
Department of Family Medicine, Aminu Kano Teaching Hospital, PMB 3452, Zaria Road, Kano
Nigeria

Abstract

Context: Nutrition is a significant factor in determining the health of older people because it affects almost all organs and systems, which could lead to varieties of diseases and premature death. Aim: To determine the nutritional status and its association with the morbidity patterns of elderly patients. Settings and Design: A cross-sectional hospital-based descriptive study involving 348 patients aged 60 years and above who presented at the Family Medicine Clinic. Subjects and Methods: Data of the socio-demographic profile, anthropometric measurements and clinical diagnosis were collected. The co-morbidities were classified based on the number, duration and affected organ or system. The nutritional status was assessed with the Mini-Nutritional Assessment tool. Statistical Analysis: Chi-square test and logistic regression analysis were used to determine associations between nutritional status and morbidity patterns of the elderly. The level of significance was set at a P ≤ 0.05. Results: A total of 348 respondents were recruited with 60.9% of females and mean age of 67.83 (standard deviation ± 7.53) years. The prevalence of malnutrition was 25.3% and of risk of malnutrition 56.6%. Furthermore, the prevalence of multi-morbidity was 74.4%. Advanced age (odd ratio = 8.911, confidence interval [CI] = 1.992–39.872, P = 0.004), underweight (OR = 1.167, CI = 0.291–37.846, P < 0.001), lack of formal education, (OR = 1.569, CI = 0.357–0.908, P = 0.018), low monthly income (OR = 1.975, CI = 1.376–2.836, P < 0.001), chronic respiratory diseases (OR = 4.250, CI = 4.025–4.492, P < 0.001) and physical inactivity (OR = 2.466, CI = 1.063–5.722, P = 0.036) were the predictors of malnutrition. Furthermore, the duration of chronic disease for more than 10 years (OR = 1.632, CI = 0.408–0.979, P = 0.040) was significantly associated with at-risk of malnutrition. Conclusion: The study revealed advanced age, underweight, low educational status, chronic respiratory diseases and physical inactivity as independent risk factors for malnutrition among the elderly.



How to cite this article:
Olawumi AL, Grema BA, Suleiman AK, Omeiza YS, Michael GC, Shuaibu A. Nutritional status and morbidity patterns of the elderly in a Northwestern Nigerian hospital: A cross-sectional study.Niger Postgrad Med J 2021;28:160-168


How to cite this URL:
Olawumi AL, Grema BA, Suleiman AK, Omeiza YS, Michael GC, Shuaibu A. Nutritional status and morbidity patterns of the elderly in a Northwestern Nigerian hospital: A cross-sectional study. Niger Postgrad Med J [serial online] 2021 [cited 2021 Dec 7 ];28:160-168
Available from: https://www.npmj.org/text.asp?2021/28/3/160/328772


Full Text



 Introduction



The world's population is ageing.[1] Population ageing 'refers to the process by which the elderly population becomes a proportionally larger component of the population.'[2] It results from the demographic transition from higher to the lower level of fertility and birth rate.[3] This was originally a phenomenon of the developed world, but recent studies have shown similar occurrences in developing countries.[4],[5] It was postulated that about two billion people in the world will be over 60 years of age by the year 2050.[6] Nigeria is expected to be the only African country that will have an elderly population of more than 15 million by the year 2025.[7],[8]

Nutrition is an important determinant of health and age-related changes in older people because it has the capacity to affect almost all human organs and systems.[9] It is associated with varieties of non-communicable diseases which could lead to premature death.[9] Researches have shown the important relationship between nutritional status and a many morbid conditions like cancers, heart diseases and dementia in the elderly.[9],[10],[11] This is because nutritional compromise predisposes elderly people to multiple co-morbidities, which later contribute to the overall well-being and nutritional impairment, thus creating a vicious cycle.[10],[11] This was attributed to the effects of chronic illnesses on dentition, eating habits, swallowing, appetite and mobility of the elderly.[10]

A systematic review in Hawaii reported that depression and diseases associated with swallowing and chewing difficulties are the most consistent factors associated with malnutrition among nursing home elderly patients.[12] A similar study in Belgium reported Parkinson's disease, constipation, depression and diseases linked with poor appetite and swallowing difficulties as the most significant co-morbid factors related to nutritional impairment in older people.[13] Furthermore, a study in Ibadan, southwestern Nigeria, reported that hypertension, osteoarthritis and psychosomatic diseases were significantly associated with under-nutrition in the elderly.[7]

This study assessed the associations between the nutritional status of the elderly and the pattern of co-morbidities in three different dimensions, which has not been done before. These dimensions include the number, duration and organ or system affected by the co-morbidities. Hence, the study is aimed at providing information on the relationship between the nutritional status and morbidity patterns among the elderly population so as to raise physicians awareness about this important association and the need to incorporate nutritional assessment in the comprehensive evaluation of the older persons. This could also provide data for further studies.

In this study, the nutritional status of the elderly patients was assessed with the Mini-Nutritional Assessment (MNA) tool, which is a well-validated tool and has been demonstrated to have an accuracy of 98% when compared with a comprehensive nutritional assessment, which includes biochemical tests, anthropometric measurements and dietary assessment.[14] This MNA tool has 18 items, which include anthropometric measurements, dietary history, clinical assessment of lifestyle habits, medication, mobility, neuropsychological problems, and self-perception of nutrition and health.[14]

 Subjects and Methods



This descriptive cross-sectional study was conducted in the Family Medicine Clinic (FMC) of Aminu Kano Teaching hospital, Kano, from 5th October, 2020 to 28th December, 2020. Kano, which is the largest commercial center in Northern Nigeria, attracts population diverse in religion, ethnicity and occupation. The hospital has 20 departments with 700 beds' capacity. It serves as referral center to the neighboring states. The FMC is the primary care unit of the hospital, where all patients except emergencies are assessed, treated and referred to other sub-specialty units of the hospital. Based on hospital records, about 250 patients were seen daily, with the elderly constituting about 10% (25).

The study population comprised patients aged 60 years and above who presented at the clinic over 12 weeks. Consenting elderly patients attending the clinic during the study period were recruited. However, those who are critically ill or with major neuropsychiatric illness such as schizophrenia were excluded from the study as they might not cooperate with the research processes.

Sample size estimation

The sample size was estimated using the formula[15] n = Zα2pq/d2 where; n = minimum sample size, Zα = standard normal deviate corresponding to a 5% level of significance (1.96), P = (61.9%, prevalence rate of malnutrition among elderly patients attending the GOPC of UCH Ibadan, Nigeria).[7]

q = 1 − P (38.1%), the proportion of the elderly who are not malnourished.

d = level of precision which was set as 5%.

The hospital record revealed an average of 25 elderly patients seen daily in the FMC; therefore, the sampling frame was 2100 (25 × 7 × 12). This formula[15] ns = n/1+ (n/N) was then used to adjust the sample size to 348 (for population <10,000 with anticipated 90% response rate).

Sampling method

A systematic random sampling method was used to recruit 348 elderly patients attending the hospital within the sampling frame of 2100 and sample interval of 6 (2100/348). At the registration of each clinic day, a trained Research Assistant identified all elderly patients who had completed registration for possible recruitment. On the 1st day, the first respondent was chosen through balloting thereafter, every sixth elderly patient was recruited if he or she fulfilled the inclusion criteria.

Data collection

The study involved two stages: Clinical evaluation and administration of a questionnaire.

The clinical evaluation involved detailed history and physical examination. Investigations such as fasting blood glucose, lipid profile, urinalysis, electrolyte urea and creatinine, packed cell volume and plain radiographs were offered based on their clinical presentation to confirm the diagnosis.

A pretested, interviewer-administered semi-structured questionnaire was then administered to the respondents by the Researcher or Research Assistant, who was a Resident Doctor in the Department of Family Medicine. Respondents' folder was serialised with numbers written on them to avoid repetition. Information was confirmed from the patients' files or caregivers whenever necessary. The socio-demographic characteristics included gender, marital status, ethnicity, religion, literacy level, living condition and occupation, and were assessed with the closed-ended question. Age and monthly income were evaluated with open-ended questions. Age was determined by the direct recall, age at marriage, age at birth of first child or in relation to historical events.

The anthropometric examinations included height, weight, mid-arm circumference and calf circumference (CC). The height and weight were measured using stadiometer and weighing scale manufactured by Seca Corporation® (Germany), and the measurements were made to the nearest 0.1 cm and 0.1 kg, respectively. In elderly patients with spinal curvatures or wheelchair bound, the half arm-span was used to estimate the height, which is the distance from the midline at the sternal notch to the tip of the middle finger. Height was then calculated by doubling the half arm span.[14] The CC and the mid-arm circumference were measured with a fiber-glass tape rule and the measurement was recorded to the nearest 0.1 cm. The body mass index (BMI) of each subject was calculated with the formula (weight [kg]/height [m2]), and classified according to the WHO classification of obesity.[16] The nutritional status was assessed with the MNA tool, which has 18 items. The assessment score was graded as; malnutrition <17; at risk of malnutrition 17–23.5; and well nourished; 23.6–30.[7],[14]

Blood pressure (BP) was measured following 5 min of quiet sitting. It was measured with an appropriately sized cuff mercury sphygmomanometer of the Accosson® UK brand and a Litmann® stethoscope on the left arm, which was supported at the level of the heart with the other arm bared and the legs uncrossed. The BP was recorded as average of two readings 5–10 min apart. Elevated BP was taken as ≥140/90 mmHg. Hypertension was then classified according to the eighth report of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High BP.[17]

The diagnosis of the chronic diseases made by the clinicians in the respondents' previous visits (as observed in their files) and those made at present were classified using the international classification of diseases-10.[18] This classification distributed the diseases into the affected organs or systems such as musculoskeletal, eye, respiratory, cardiovascular (CV) or the circulatory, skin, endocrine or nutrition, ENT, infections and others.[18] The respondents with two or more chronic diseases were classified to have multimorbidity. The duration of morbidities was classified using the cumulative duration of diagnosis of the chronic diseases in each respondent.

Ethical considerations

Ethical approval was obtained from the Research Ethical Committee of the hospital (No. NHREC/21/08/2008/AKTH/EC/1842). Respondents discovered to have nutritional problems during the study were provided with adequate counselling and care as appropriate. Those with morbidities were managed and those requiring other specialist care were referred appropriately.

Statistical analysis

Data were collated, coded and analysed using the Statistical Package for the Social Sciences (SPSS) version 22 software. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp. Absolute numbers and simple percentages were used to describe categorical variables such as morbidity classes and nutritional status. Similarly, quantitative variables (such as weight, height and MAC) were described using measures of central tendency (mean) and measures of dispersion (range, standard deviation [SD]) as appropriate. The qualitative variables (such as sex, occupation and educational level) were expressed in frequencies and percentages. The Chi-square test was used to assess the significance of associations between categorical variables. A P ≤ 0.05 was considered statistically significant. Variables that were significant on bivariate analysis were subjected to logistic regression to assess the predictors of malnutrition.

 Results



The ages of the respondents ranged from 60 to 95 years with a mean age of 67.83 (SD ± 7.53) years. As shown in [Table 1], the majority (78.2%) of the respondents belong to the age group (60–74 years), while 17.5% belonged to the age group (75–84 years) and 4.3% were above 85 years. The patients were predominantly females (60.9%) of the Hausa tribe (58.9%) and Muslims (94.3%). The majority were married in polygamous (78.4%) family setting. The majority (73.6%) had no formal education and 57.2% earned below ₦30,000 (70USD) per month [Table 1].{Table 1}

As shown in [Table 2], the majority of the respondents did not smoke (87.1%) or take alcohol (98.3%). Furthermore, only (2.0%) of the respondents were physically active. Thus, the prevalence of physical inactivity in this study is 98%. The mean BMI of the participants was 25.03 (SD ± 6.36) kg/m2 with a range of 13.50–59.65 kg/m2. A total of 37 (10.6%) respondents were underweight and 157 (45.1%) were overweight [Table 3]. As shown in [Table 4], 63 (18.1%) respondents had normal nutrition, 197 (56.6%) were at risk of malnutrition and 88 (25.3%) were malnourished. Thus, the prevalence of malnutrition was 25.3%.{Table 2}{Table 3}{Table 4}

CV diseases were the most prevalent morbidity (88.5%) among the respondents, followed by the diseases of the musculoskeletal system (42%). Hypertension was the most prevalent (50%) among all the CV diseases. Significant percentage of the respondents (38.2%) was diagnosed with their chronic illnesses for more than 10 years. The prevalence of multimorbidity in this study is 74.4% [Table 5].{Table 5}

[Table 6] shows the association between nutritional status and socio-demographic characteristics of the respondents. The association among age, tribe, educational level, occupation, monthly income, family type and nutritional status was statistically significant.{Table 6}

As shown in [Table 7] and [Table 8], also physical exercise (χ2 = 26.440, P < 0.001) and BMI (χ2 = 103.550, P < 0.001) had a significant association with nutritional status. The respondents who did not engage in exercise were found to have a higher proportion of malnutrition (35.8%) as compared to those on regular exercise (0.0%). The undernourished respondents had the highest rate of malnutrition (81.1%).{Table 7}{Table 8}

As highlighted in [Table 9], there was significant association between nutritional status and chronic respiratory diseases, multimorbidity and duration of chronic illnesses. The proportion of malnutrition was higher (36.1%) among the respondents diagnosed with chronic disease for >10 years than those for <5 years (17.1%). Furthermore, 87.5% of respondents with chronic respiratory diseases were malnourished. Similarly, 56.4% of respondents with multimorbidity were at-risk of malnutrition and 27.8% were malnourished.{Table 9}

Logistic regression of the associated factors with nutritional status in [Table 10] revealed that advancing age, lack of formal education, low monthly income, physical inactivity, underweight and chronic respiratory diseases were the independent determinants of malnutrition among the elderly. Furthermore, the long duration of chronic diseases (>10 years) was the only determinant for at-risk of malnutrition in this study.{Table 10}

 Discussion



This study has provided two main groups of data: An epidemiological picture [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]; and associations' analyses between nutritional status and many demographic data and clinical parameters [Table 6], [Table 7], [Table 8], [Table 9]. In [Table 10], there is the main synthesis of the relevant associations, which was the essential value of the study.

The prevalence of malnutrition was 25.3% and of at-risk of malnutrition was 56.6%. These data are high and similar to that reported by Ferdous et al. in Bangladesh, where 26% were malnourished and 55% were at risk.[19] It is also comparable to 22.8% for malnutrition reported in a multinational study and 20.8% reported by Joymati et al. in India.[20],[21] The similarity between our study and that of Bangladesh and India may be due to similar socio-demographic characteristics of developing countries which include poor income and housing, low literacy level and consequently, high disease burden.[22] In contrast, a lower prevalence of 13% for malnutrition and 31% for at-risk group were reported by Saka et al. in Turkey, which may be because Turkey is a developed country with high income and literacy level.[22],[23] Oliveira et al. reported a higher prevalence of 29.1% for malnutrition but lower prevalence of 37.1% for at-risk group among hospitalised elderly in Brazil.[24] This could be because nutritional status deteriorates as dependency and care need increases.[25] Hence, malnutrition is higher among hospitalised or institutionalised elderly than in outpatient. Naidoo et al. in South Africa also reported a lower malnutrition prevalence of 5.5% and at-risk group prevalence of 43.4%.[26] This may be because the study was done in a community setting where older people lived autonomously with limited dependence compared to the hospitalised due to chronic diseases.

The prevalence of physical inactivity in this study was 98% which was comparable to that reported in Saudi Arabia (96.1%) but higher than the global prevalence of 21.4% and that reported in India (49.7%) and the United states (34.6%).[27],[28],[29],[30] This very high level of physical inactivity in this study could be related to the decrease in the activity of daily living with advancing age.[30] Furthermore, high level of illiteracy among the study participants, coupled with the community perceptions and cultural restrictions of the elderly from active life, could discourage them from participating in physical exercise.

The prevalence of underweight, overweight and obesity as defined by BMI were 10.6%, 27.6% and 17.5%, respectively. The prevalence of underweight is higher than 4.8% but lower than 54.1% for overweight reported by Adebusoye et al. in Ibadan, South-western, Nigeria.[31] Similar lower prevalence of 3.2% for underweight but higher prevalence of 29% for overweight and 33.8% for obesity was reported by Adriana in Romania.[32] This could be due to the high level of poverty, illiteracy and harmful cultural practices in developing countries like Nigeria with high preponderance to the northern region.[33],[34] Similar high prevalence of 40% for overweight was also reported by Hajek et al. in Germany.[35] This could be due to lifestyle and genetic factors that have made overweight and obesity an epidemic in many parts of Europe.[36]

The prevalence of multi-morbidity was 74.4% and hypertension was the most common (50%) morbidity among the respondents. This is similar to 74% reported by Hewitt et al. in the United Kingdom and also comparable to 65% and 68.4% reported in Burkina Faso and North-central, Nigeria, respectively.[37],[38],[39] These studies also reported hypertension as the most prevalent morbidity. The high prevalence of multi-morbidity in older persons could be attributed to the progressive increase in the level of physical inactivity with advancing age, which is a major determinant of metabolic and CV diseases in both developed and developing countries.[38]

CV diseases were the most prevalent morbidity (308; 88.5%) among the respondents, followed by the diseases of the musculoskeletal system (146; 42%). Most respondents (133; 38.2%) were diagnosed with their chronic illnesses for more than 10 years.

The higher prevalence of CV diseases such as hypertension identified in this study was in tandem with other studies.[40],[41],[42],[43] This has become a major public health concern as BP rises with age in almost all populations.[40],[42]

The high prevalence of musculoskeletal problems, especially among women was also similar to other studies and it could be due to hormonal withdrawal and attendant osteoporosis.[43],[44]

The strong relationship between advancing age and malnutrition identified in this study was also found in several literatures.[6],[7],[10],[12],[13] This could be due to the physiological and pathological changes associated with advancing age. These changes result in the development of co-morbid illness, functional impairment, feeding problems and consequently malnutrition.[10] Also, the strong relationship between malnutrition and low income or financial dependency, and lower educational status is consistent with other researches.[26],[45],[46],[47] This may be because intake and even choices of food depend on the knowledge and awareness about its nutritional importance and of course, the purchasing power.

This study also reported a significant association between malnutrition and physical inactivity. Nutritional status of the elderly worsens with decreasing physical activity, such that none among those on regular exercise was malnourished while 15.2% and 35.8% of those not regular on exercise and those not exercising at all were malnourished, respectively. Al-Zeidaneen et al in Jordan and Whittaker et al in the United Kingdom reported similar findings.[48],[49] This decreasing physical activity was attributed to decreased muscle mass and strength with ageing.[49],[50]

Underweight was one of the identified determinants of malnutrition among the elderly in this study. The rate of malnutrition was highest (81.1%) among the underweight elderly. Similar findings were reported in a systematic review by Fávaro- Moreira et al and in a community based cross-sectional study by Boscatto et al in southern Brazil.[13],[51]

Chronic respiratory disease was also a determinant of elderly nutrition. Although there was no study to compare with, nutrition experts explained that 'lung diseases exert a negative impact on nutritional status, especially among older patients where aging per se is already associated with relevant changes in nutrient intake, metabolism, and body composition.'[51],[52]

The risk of developing malnutrition among the respondents increases with the increasing duration of chronic illnesses (>10 years). A similar finding was reported by Bell et al. in a systemic review and in a cross-sectional study by Singh and Shrestha among elderly living in an old age home in Nepal.[53],[54] This was attributed to increase in the risk of chronic drug usage, frequent visits in hospital and consequently, a higher possibility for hospitalization or institutionalization.[54] Therefore, periodic nutritional screening is essential for elderly patients, especially females and those at advanced age so as to comprehensively examine, identify and treat predisposing factors to malnutrition in them.

The study has some limitations. The biochemical and hematological parameters of nutritional status were not assessed. Temporal bias could not be eliminated and the findings are limited to urban out-patient settings. Despite these limitations, the data generated from this study will contribute to scientific evidence and provide indirect reasons for instituting nutritional screening on elderly patients in our clinics and primary care settings.

 Conclusion



The study reports high prevalence of malnutrition and at-risk group. It also reveals advanced age, underweight, low educational status, chronic respiratory diseases and physical inactivity as the independent risk factors for malnutrition. Therefore, interventions to reduce malnutrition in the elderly in similar settings may require consideration of these important risk factors.

Acknowledgement

We acknowledge the role of the research assistants and department's secretarial staffs in making this study a reality.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

References

1WHO. Ageing and Nutrition: A Growing Global Challenge. Available from: http://www.who.int/nutrition/topic/ageing/index1. [Last accessed on 2019 Sep 14].
2Joubert J, Bradshaw D. Population ageing and health challenges in South Africa. Cape Town Technical Report. S Afr Med Res Counc 2006;1:204-5.
3Amarya S, Kalyani S, Manisha S. Changes during ageing and their association with malnutrition. J Clin Gerontol Geriatr 2015;6:78-84.
4Ahmed T, Haboubi N. Assessment and management of nutrition in older people and its importance to health. Clin Interv Aging 2010;5:207-16.
5Asagba A. Research and the formulation and implementation of ageing policy in Africa: The case of Nigeria. Gener Rev 2005;15:39-41.
6WHO. Elderly People: Improving oral Health Amongst the Elderly. Available from: http://www.who.int/oral health/action/groups/en/index1. [Last accessed on 2019 Oct 03].
7United Nations. World Population Ageing Report. Available from: http://www.un.org/ageing/wpa2015/report.html. [Last accessed on 2019 Nov 04].
8National Population Commission. 2006 Population and Housing Census. Vol. 4. Abuja: National Population Commission; 2010. p. 3.
9McNaughton SA, Crawford D, Ball K, Salmon J. Understanding determinants of nutrition, physical activity and quality of life among older adults: The Wellbeing, Eating and Exercise for a Long Life (WELL) study. Health Qual Life Outcomes 2012;10:109-10.
10Agarwalla R, Saikia AM, Baruah R. Assessment of the nutritional status of the elderly and its correlates. J Family Community Med 2015;22:39-43.
11Gureje O, Kola L, Afolabi E, Olley BO. Determinants of quality of life of elderly Nigerians: Results from the Ibadan study of ageing. Afr J Med Med Sci 2008;37:239-47.
12Tamura BK, Bell CL, Masaki KH, Amella EJ. Factors associated with weight loss, low BMI, and malnutrition among nursing home patients: A systematic review of the literature. J Am Med Dir Assoc 2013;14:649-55.
13Fávaro-Moreira NC, Krausch-Hofmann S, Matthys C, Vereecken C, Vanhauwaert E, Declercq A, et al. Risk factors for malnutrition in older adults: A systematic review of the literature based on longitudinal data. Adv Nutr 2016;7:507-22.
14Nestle. Malnutrition in Older Adult. Available from: http://www.nestle.com/library/events/facts.html. [Last accessed on 2019 Oct 04].
15Charan J, Biswas T. How to calculate sample size for different study designs in medical research? Indian J Psychol Med 2013;35:121-6.
16WHO. Ageing and Nutrition: A Growing Global Challenge. Available from: http://www.who.int/nutrition/topic/ageing/index1. [Last accessed on 2019 Jul 14].
17Abel N, Contino K, Jain N, Grewal N, Grand E, Hagans I, et al. Eight joint national committee (JNC-8) guidelines and the outpatient management of hypertension in the African-American Population. N Am J Med Sci 2015;7:438-45.
18ICD-10-CM. Clinical Modification. Available from: http://www.who.int/classifications/icd/icdonlineversions/en. [Last accessed on 2019 Jul 24].
19Ferdous T, Kabir ZN, Wahlin A, Streatfield K, Cederholm T. The multidimensional background of malnutrition among rural older individuals in Bangladesh – A challenge for the Millennium Development Goal. Public Health Nutr 2009;12:2270-8.
20Kaiser MJ, Bauer JM, Ramsch C, Uter W, Guigoz Y, Cederholm T et al. Mini Nutrition Assessment International Group. Frequency of malnutrition in older adults: A multinational perspective using the mini nutritional assessment. J Am Geriatr Soc 2010;58:1734-8.
21Joymati O, Ningombam M, Rajkumari B, Gangmei A. Assessment of nutritional status among elderly population in a rural area in Manipur: Community-based cross-sectional study Int J Community Med Public Health 2018;5:3125-9.
22WHO. Projections of Mortality and Burden of Disease, 2004-2030. Available from: http://www.who.int/healthinfo/global_burden_disease/projections/en/index.html. [Last accessed on 2018 Sep 10].
23Saka M, Kaya O, Ozturk GB, Entei N, Kara MA. Malnutrition in the elderly and its relation with other geriatric syndrome. J Clin Nutr 2010;29:745-8.
24Oliveira MR, Fogaça KC, Leandro-Merhi VA. Nutritional status and functional capacity of hospitalized elderly. Nutr J 2009;8:54.
25Milne AC, Potter J, Avenell A. Protein and energy supplementation in elderly people at risk from malnutrition. Cochrane Database Syst Rev 2005;2:CD003288.
26Naidoo I, Charlton KE, Esterhuizen TM, Cassim B. High risk of malnutrition associated with depressive symptoms in older South Africans living in KwaZulu-Natal, South Africa: A cross-sectional survey. J Health Popul Nutr 2015;33:19-20.
27Amiin TT, Alkhondair AS, Al Harbi MA, Al Ali AR. Leisure time physical inactivity in Saudi Arabia: Prevalence, pattern and determining factors. Asian Pac J Cancer Prev 2012;13:351-60.
28Newtonraj A, Murugan N, Singh Z, Chauhan RC, Velavan A, Mani M. Factors associated with physical inactivity among adult urban population of Puducherry, India: A population based cross-sectional study. J Clin Diagn Res 2017;11:C15-7.
29Dumith SC, Hallal PC, Reis RS, Kohl HW 3rd. Worldwide prevalence of physical inactivity and its association with human development index in 76 countries. Prev Med 2011;53:24-8.
30Bassett DR. Trends in physical activity. Am J Med 2014;12:019.
31Adebusoye LA, Ajayi IO, Dairo MD, Ogunniyi AO. Factors associated with undernutrition and over weight in elderly patients presenting at a primary care clinic in Nigeria. S Afr Fam Pract 2011;53:355-60.
32Adriana G. Prevalence of obesity in a group of elderly. Eur Sci J 2014;10:28-40.
33Srinivasan K, Vaz M, Thomas T. Prevalence of health related disability among community dwelling urban elderly from middle socioeconomic strata in Bengaluru, India. Indian J Med Res 2010;131:515-21.
34National Population Commission (NPC) [Nigeria] and ICF International. 2014. Nigeria Demographic and Health Survey 2013. Abuja, Nigeria, and Rockville, Maryland, USA: NPC and ICF International. 2014:16-9.
35Hajek A, Lehnert T, Ernst A, Lange C, Wiese B, Prokein J, et al. Prevalence and determinants of overweight and obesity in old age in Germany. BMC Geriatr 2015;15:83.
36WHO. Country Profile (Europe) of Overweight and Obesity. Available from: https://www.europ.who.int.country-profile.pdf. [Last accessed on 2020 Jan 19].
37Ngbea GT, Achunike HC. Poverty in northern Nigeria. Asian J Res Soc Sci Humanit 2014;2:266-71.
38Hewitt J, McCormack C, Tay HS, Greig M, Law J, Tay A, et al. Prevalence of multimorbidity and its association with outcomes in older emergency general surgical patients: An observational study. BMJ Open 2016;6:e010126.
39Hien H, Berthe A, Drabo MK, Meda N, Konate B, Tou F, et al. Prevalence and pattern of multimorbidity among elderly in Burkina Faso: Cross-sectional study. Trop Med Int Health 2014;19:1328-33.
40Ejim EC, Okafor CI, Emehel A, Mbah AU, Onyia U, Egwuonwu T, et al. Prevalence of cardiovascular risk factors in the middle-aged and elderly population of a nigerian rural community. J Trop Med 2011;2011:308687.
41Parray SH, Ahmed D, Ahmed M, Gaash B. Morbidity profile of geriatric population in Kashmir (India). Indian J Pract Dr 2008;4:1-2.
42Kishore S, Ruchi J, Semwal J, Chandra R. Morbidity profile of elderly persons. J Med Educ Res 2007;9:87-9.
43Woo EK, Han C, Jo SA, Park MK, Kim S, Kim E, et al. Morbidity and related factors among elderly people in South Korea: Results from the Ansan Geriatric (AGE) cohort study. BMC Public Health 2007;7:10.
44Abdulraheem IS, Abdulrahman AG. Morbidity pattern among elderly population in a Nigerian tertiary health care institution: Analysis of a retrospective study. Nigerian Med Pract 2008;54:32-8.
45Ogunniyi A, Baiyewu O, Gureje O, Hall KS, Unverzagt FW, Oluwole SA, et al. Morbidity pattern in a sample of elderly Nigerian resident in Idikan community Ibadan. West Afr J Med 2001;20:227-31.
46Lahiri S, Biswas A, Santra S, Lahiri SK. Assessment of nutritional status among elderly population in the rural areas of West Bengal, India. Int J Med Sci Public Health 2015;4:569-72.
47Ghimire S, Baral BK, Callahan K. Nutritional assessment of community-dwelling older adults in rural Nepal. PLoS One 2017;12:e0172052.
48Al-Zeidaneen SA, Al-Bayyari NS, Ismail Y. Effect of physical activity and gender on malnutrition risk among a group of elderly Jordanians. Pak J Nutr 2017;16:708-13.
49Whittaker AC, Delledonne M, Finni T, Garagnani P, Greig C, Kallen V, et al. Physical Activity and Nutrition INfluences In ageing (PANINI): Consortium mission statement. Aging Clin Exp Res 2018;30:685-92.
50Pierik VD, Meskers CG, Van Ancum JM, Numans ST, Verlaan S, Scheerman K, et al. High risk of malnutrition is associated with low muscle mass in older hospital patients – A prospective cohort study. BMC Geriatr 2017;17:118.
51Boscatto EC, Duarte Mde F, Coqueiro Rda S, Barbosa AR. Nutritional status in the oldest elderly and associated factors. Rev Assoc Med Bras (1992) 2013;59:40-7.
52Berthon BS, Wood LG. Nutrition and respiratory health – Feature review. Nutrients 2015;7:1618-43.
53Bell C, Tamura BK, Masaki KH, Amella EJ. Prevalence and measures of nutritional compromise among nursing home patients: Weight loss, low BMI, malnutrition and feeding dependency – A systemic review of the literature. J Am Med Dir Assoc 2013;14:94-100.
54Singh DR, Shrestha S. Nutritional status of the senior citizens living in the old age homes at Kathmandu metropolitan municipality in Nepal. Int J Community Med Public Health 2016;3:1707-15. [doi: 10.18203/2394-6040.ijcmph/2016/2032].