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 Table of Contents  
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

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

Date of Submission05-May-2021
Date of Decision07-Aug-2021
Date of Acceptance11-Aug-2021
Date of Web Publication22-Oct-2021

Correspondence Address:
Dr. Abdulgafar Lekan Olawumi
Department of Family Medicine, Aminu Kano Teaching Hospital, PMB 3452, Zaria Road, Kano
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/npmj.npmj_545_21

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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.

Keywords: Elderly patients and North-western Nigeria, morbidity patterns, nutritional status

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;28:160-8

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 1];28:160-8. Available from: https://www.npmj.org/text.asp?2021/28/3/160/328772

  Introduction Top

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 Top

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 Top

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: Sociodemographic characteristics

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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: Lifestyle pattern

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Table 3: Body mass index

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Table 4: Nutritional status

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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: Morbidity patterns

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[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: Sociodemographic characteristics and nutritional status

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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: Lifestyle and nutritional status

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Table 8: Body mass index and nutritional status of the respondents

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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: Morbidity patterns and nutritional status

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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: Logistic regression analysis of the factors associated with malnutrition

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  Discussion Top

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 Top

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.


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

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

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  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8], [Table 9], [Table 10]


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