Top Links
Journal of Nutrition and Health Sciences
ISSN: 2393-9060
Dietary Intake, Anthropometric Characteristics and Clinical Assessment of Elderly in Ondo State, Nigeria
Copyright: © 2017 Ogundahunsi GA. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Related article at Pubmed, Google Scholar
This study was designed to assess the nutrition status of the elderly in Ondo State Nigeria. Random sampling techniques were used to select 1155 elderly for this study. Socio-demographic characteristics, clinical assessment, food consumption pattern, anthropometric measurements of the elderly were determined. Data entry and analysis were done with the use of scientific instruments. This involved the SPSS version 17. It detailed the analytical tools, including frequencies, percentage and correlations. The result showed that Intake of nutrients by the elderly was shown to be inadequate. Protein containing foods intake was low, as 4% of the elderly took milk daily while 8.3% and 4% took organ meat and fleshy foods daily. Anthropometric assessment as indicated by MUAMA mean and standard deviation (23.80±54.203, 25.50±62.001 for male and female respectively) and MUAFA mean and standard deviation (12.00±23.063, 14.90±48.105 for male and female respectively) showed that the females’ elderly were having normal skin fold thickness as well as BMI but the males’ MUAMA and MUAFA indicated wasting. The clinical assessment tool for the elderly revealed various form of sign and symptoms of malnutrition. Night blindness was 61.03%, angular stomatitis was 7.1%, and joint pains were 41.03% and 7.01 % had dementia. The result showed the correlation between some variables and nutritional status of the elderly. Age and BMI (r=-0.26, p=0.05); socio-economic status and milk intake (r=0.46, p=0.05); protein intake and muscle wasting (r=0.46, p=0.05); fruits and vegetable intake and constipation (r=0.52, p=0.05). The study concluded that micro-nutrient deficiency was prevalent among the elderly studied. Therefore recommended that, government intervention is needed to improve the quality of life of the elderly. Also, there should be organized nutrition education among the elderly on adequate diet.
Keywords:Dietary Intake; Anthropometric Characteristics, Clinical Assessment, Elderly
The United Nations defined the elderly as those in age 60 years and above [1]. Nigeria, like other African countries should see the rapid expansion of aging population as a serious future challenge. The population of elderly in Ondo State, Nigeria is 128,053 this made up the 3.7% of total population of Ondo State [2]. It is anticipated that the increasing elderly population would lead to more resources to be devoted to various health and nutritional challenges in the developing countries [3]. The physiological and psychological changes that occur among elderly have nutritional implications but the efforts of government and non-governmental organization on this age group are not pronounced as it is in other age groups.
Nutritional changes facing the elderly as a result of changes associated with their age must be managed through dietary means. Instead of the older adult receiving adequate nutrition to meet up with nutrition demand of the present physiological status, reverse is the case especially in the developing countries. The nutritional status is either too low or too high, which usually leads to health complication among the elderly. Revealed that 5-10% of elderly people living in the community setting are malnourished [4]. Nutritional status assessment of the elderly should be the first step taken in determining the policy framework for elderly wellbeing in Nigeria.
Malnutrition is becoming increasingly more common among the elderly population [5]. Also, [6] discovered malnutrition among 42.2% of elderly population assessed for morbidity pattern in a Nigeria health care institution The nutritional status of elderly have not been adequately studied in Ondo State, whereas its importance to health policy framework cannot be over-emphasized, hence this research.
• To verify pattern of feeding, food intake as well as nutrients composition of the food of the elderly in Ondo State in order to establish a profound solution to situation of malnutrition among elderly
• To determine body composition of the elderly, using anthropometric indices
• To examine physical manifestation of malnutrition among the elderly
The population of Ondo Sate according to [7] and [2] revealed that the population was three million, four hundred and sixty thousand and eight hundred and seventy seven (3,460,877).
Multistage sampling techniques were involved in this study in order to get the participants for the study. Ondo State was purposively selected because literature indicated low nutrition status among elderly in Ondo State but the causes of low nutrition status was not identified [8]. The research was conducted at three geo-political zones of Ondo State known as Senatorial Districts. These are; Ondo South, Ondo Central and Ondo North Senatorial Districts, each Senatorial District consists of six Local Government Areas (LGAs). Three Local Government Areas (LGAs) were selected out of the eighteen LGAs in the three Senatorial Districts (one from each Senatorial District) using simple random sampling method. Also, simple random sampling was used to select households with eligible participants. A total of three hundred and eighty five elderly was selected from each LGA which made up the total of one thousand five hundred and fifty five (1,155) elderly from the three Senatorial Districts. This means 0.9% of the total elderly population (128,053) was used as the sample size for the study.
The target population in this study is the elderly people in Ondo State with age 60 years and above.
The Kish-Leslie [9] formula: n0=Z2pq⁄e2
no= estimated necessary sample size z = the standard normal deviates p = the estimated proportion of incidence of cases in the population q = confidence level e = the proportion of the sample error in a given population i.e. tolerable amount of error At prevalence of 0.037 (prevalence of elderly in Ondo State 3.7%) was used to obtain the population of 1039.5 for the three Senatorial Districts and 10% of non-response 115.5 was added to make it 1155.
Skin fold caliper, food models, dietary diversity score, Diagnostic scale, Height-o-meter, Non stretched tape and structured questionnaire.
The structured questionnaire accompanied with food models was used to determine (i) Food intake (food history and rated using food diversity score). (ii) Clinical Assessment; clinical examination such as abnormal changes in skin, eyes, muscle and other parts of the body was conducted to determine signs of vitamins and mineral deficiencies. This was assessed by physical examination of part of the body by trained personnel. Also, doctor’s report presented by some of the respondents helped in determining their health condition.
Anthropometric assessment was taken using skin fold caliper, diagnostic weighing scale, height-o-meter and non-stretched tape. Height, weight and arm span were measured according to internationally accepted standard and protocol [10]. Arm span was used where the participant can no longer stand erect. Body composition was determined using [11] equation;
MUAMA = MUAC – π × TSF ⁄ 10
Although India lies in the tropical region and is believed to have adequate sunlight around the year, it must be noted that Vitamin D sufficiency via sun exposure may not be a rational solution for most Indians. For adequacy, an individual’s bare skin should be exposed to sunlight to photosynthesize vitamin D. Indians naturally have darker skin that has high melanin content. This melanin tends to acts as a natural sunscreen. Therefore, in comparison to individuals with fairer skin, such as Caucasians, darker skin produces a significantly lesser amount of vitamin D. Urbanization also has a part to play in causing vitamin D deficiency. Overcrowded living environment often prevents direct sunlight from reaching the homes in cities. Added to this is the atmospheric pollution of metropolitan cities, spending majority of the time at work indoors, the limited outdoor activities and the use of sunscreen and umbrellas to protect the skin from the scorching heat of the Indian sun [6-8,26,27]. The higher prevalence of Vitamin D deficiency in women can be attributed to many social customs prevalent in India like the use of pardah, enforced use of completely covering clothing and even social restrictions to going outdoors.
Vitamin D deficiency is known to affect 70%-100% of ostensibly healthy individuals in India. Vitamin D deficiency adversely affects the skeletal components and causes rickets in children and osteomalacia in adults. It is linked to various Oral diseases like increases caries susceptibility, predisposition to temporomandibular joint (TMJ) disorders and musculoskeletal pain [28]. The extra-skeletal ill effects of vitamin D deficiency are also innumerable. The female population is significantly more affected and this can have adverse effects on their pregnancy too. The quality of life is adversely affected in the geriatric population due to vitamin D deficiency [29]. Hence it is important that awareness should be created about adequate sun exposure to avoid deficiency. Supplementation and fortification of food may be considered a viable option when adequate exposure to sun is not possible however its feasibility may be in question. The small sample size and randomized sampling were the limitations of this study and more research must be carried out to identify the incidence of vitamin D Insufficiency and deficiency and strategies to tackling this problem.
The primary source of vitamin D remains exposure of skin to the sunlight and not dietary sources. In spite of Mumbai lying in the latitudes that offer adequate exposure to sunlight, 52% of the subjects in the study did not have adequate vitamin D levels. Urbanization, overcrowding, lifestyle changes like lack of outdoor activities along with rising pollution can be linked to this increasing vitamin D deficiency in cities. Females were found to be affected more by vitamin D deficiency and insufficiency and the cause can be traced back to a lot of social customs that restrict the exposure of “bare skin” to sunlight. With more and more research indicating the importance of Vitamin D for skeletal and extra-skeletal health efforts should be directed not only to identifying this problem but also finding rational and feasible solutions to treating vitamin D deficiency and insufficiency in the Indian population.
We would like to express our deepest gratitude to the publishers of Journal of Nutrition and Health Sciences, Annex Publishers, Manassas, Virginia, USA for providing full publication support for this work.
Variables |
Frequency (n) |
Percentage (%) |
Age (yrs) |
||
60-64 |
465 |
40.26 |
65-69 |
489 |
42.34 |
≥70 |
201 |
17.40 |
Religion | ||
Christianity |
782 |
67.70 |
Islamic |
358 |
31.00 |
Traditional |
15 |
1.30 |
Ethnicity | ||
Yoruba |
987 |
85.45 |
Ibo |
37 |
3.2 |
Ebira |
131 |
11.34 |
Sex | ||
Male |
554 |
48.00 |
Female |
601 |
52.00 |
Civil servants |
15 |
1.30 |
Private business |
213 |
18.44 |
Artisan |
56 |
4.85 |
Retired |
312 |
27.01 |
Farmer |
156 |
13.51 |
Depending on children/relatives |
403 |
34.89 |
Monthly income in Naira/Pounds (€305/naira) | ||
5000-14,000/ /16.39-45.9 |
759 |
65..1 |
15,000 -24,000/49.18-78.69 |
199 |
17.23 |
25,000- 34,000/81.96-111.48 |
25 |
2.17 |
35,000 and above114.75 above |
172 |
14.89 |
Table 1: The socio-demographic/economic characteristics of the elderly (n=1155) |
Food groups | Example | Frequency (n) | Percentage (%) | Yes=1 No=0 |
Cereals | Corn, rice, wheat, sorghum, millet or foods made from these (e.g., bread, Pap | 352 |
0.48 |
Yes=1 |
803 | 69.52 | No= 0 | ||
Tubers | White yam, white cassava, or other foods made from roots | 1054 |
91.26 |
Yes=1 |
101 | 8.74 | No=0 | ||
Vegetables | Pumpkin, carrot, okro, amaranthus, corchorus |
361 |
31.26 |
Yes=1 |
794 | 68.74 | No=0 | ||
Vitamin A rich foods | ripe mango, ripe papaya, carrots |
293 |
18.70 |
Yes=1 |
936 | 81.30 | No=0 | ||
Legumes, nut and seeds | Cowpeas, soybeans groundnut, melon seed |
568 |
49.18 |
Yes=1 |
587 | 50.82 | No=0 | ||
Organ meat | liver, kidney, heart or other organ meats |
102 |
8.83 |
Yes=1 |
1053 | 91.17 | No=0 | ||
Flesh meat | beef, pork, lamb, goat, rabbit, game, chicken, duck, other birds, insects |
46 |
4.00 |
Yes=1 |
1109 | 96.00 | No=0 | ||
Fish and fish products | fresh or dried fish or shellfish |
1034 |
89.52 |
Yes=1 |
121 | 10.48 | No=0 | ||
Milk and milk products | Milk, local cheese or yoghurt |
46 |
4.00 |
Yes=1 |
1109 | 96.00 | No=0 | ||
Oil and fat | Vegetable oil, animal fat |
1139 |
98.60 |
Yes=1 |
16 | 1.40 | No=0 | ||
Spices and condiments | Turmeric, ginger, bouillon cube |
531 |
48.57 |
Yes=1 |
624 | 54.03 | No=0 | ||
Table 2: Daily Dietary Diversity of the Elderly |
Clinical Assessment | Frequency |
Percentage (%) |
General
|
||
No symptoms |
634 |
54.90 |
Wasted, Skinny |
171 |
14.80 |
Loss of appetite |
350 |
30.30 |
Skin | ||
No skin problem |
455 |
39.39 |
Eczematous |
115 |
9.95 |
Scaling |
118 |
10.21 |
Pigmentation changes |
362 |
31.34 |
Thickness and dryness of skin |
105 |
9.09 |
Head | ||
No symptom |
782 |
67.70 |
Temporal muscle wasting |
208 |
18.00 |
Hair | ||
No symptom |
186 |
16.10 |
Spare and thin, dyspigmentation |
172 |
14.89 |
Easy to pull out |
3 |
0.26 |
Eye | ||
No symptom |
138 |
11.94 |
History of night blindness |
705 |
61.03 |
Photophobia, bluring |
289 |
25.02 |
Conjuctional, inflammation |
15 |
1.29 |
Corneal vascularization | 8 | 0.69 |
Mouth | ||
No symptom |
849 |
73.51 |
Glossitis |
17 |
1.47 |
Bleeding gums |
208 |
18.01 |
Cheilosis/angular stomatitis |
81 |
7.01 |
Problem with chewing | ||
Yes |
708 |
61.29 |
No |
447 |
38.71 |
Abdomen | ||
No symptom |
396 |
34.28 |
Constipation |
753 |
65.19 |
Hepatomegaly |
6 |
0.52 |
Bone and muscle | ||
Bone ache |
416 |
36.01 |
Osteoporosis |
28 |
2.42 |
Joint pain |
474 |
41.03 |
Neurologic | ||
Dementia |
81 |
7.01 |
Table 3: Clinical Characteristics of the Elderly |
Variables | Male Mean±SD (n=502) |
Female Mean±SD (n=653) |
Age |
69.99± 67.180 |
69.34±58.232 |
Weight (kg) |
62.26±34.598 |
59.70±51.549 |
Height (m) |
165.04±68.759 |
157.01±38.248 |
Arm span (cm) |
169.74±99.202 |
162.30±80.999 |
BMI (kg/m2) |
22.86±92.014 |
23.93±89.801 |
Waist (cm) |
39.19±73.743 |
35.01±37.601 |
Hip (cm) |
37.72±24.543 |
42.87±30.073 |
Waist/hip ratio |
1.03±68.011 |
0.81±34.579 |
Triceps (mm) |
12.48±48.281 |
14.74±80.504 |
MUAC (cm) |
21.23±67.008 |
22.53±60.091 |
MUAA(cm2) |
35.9±76.006 |
40.40±34.561 |
MUAMA(cm2) |
23.80±54.203 |
25.50±30.001 |
MUAFA(cm2) |
12.00±23.063 |
14.90±48.105 |
Table 4: Anthropometric Characteristics of the Elderly |
Variables | Nutritional status |
r | P |
Age |
BMI (anthropometric status) |
-0.26 |
0.05 |
Socio-economic status |
Milk intake (dietary intake) |
0.48 |
0.05 |
Low milk intake |
Bone ache (clinical status) |
0.36 |
0.05 |
Protein intake |
Muscle wasting (clinical status) |
0.46 |
0.05 |
Fruits and vegetable intake |
Back bone ache and joint pain (clinical status) |
0.35 |
0.05 |
Fruits and vegetable intake |
Constipation (clinical status) |
0.52 |
0.05 |
Table 5: Correlation of some Variables with the Nutritional status of the Elderly |