Frailty and Nutritional Status among Urban Older Adults in South India

T. Shalini; P. Swathi Chitra; B. Naveen Kumar; G. Madhavi; G. Bhanuprakash Reddy

doi:10.1155/2020/8763413

Frailty and Nutritional Status among Urban Older Adults in South India

Shalini, T.;Chitra, P. Swathi;Kumar, B. Naveen;Madhavi, G.;Reddy, G. Bhanuprakash 2020-07-10 00:00:00 Hindawi Journal of Aging Research Volume 2020, Article ID 8763413, 11 pages https://doi.org/10.1155/2020/8763413 Research Article Frailty and Nutritional Status among Urban Older Adults in South India 1 1 2 3 T. Shalini, P. Swathi Chitra, B. Naveen Kumar, G. Madhavi, and G. Bhanuprakash Reddy Department of Biochemistry, ICMR-National Institute of Nutrition, Jamai-Osmania, Tarnaka, Hyderabad, Telangana, India Department of Statistics, ICMR-National Institute of Nutrition, Jamai-Osmania, Tarnaka, Hyderabad, Telangana, India Department of Community Studies, ICMR-National Institute of Nutrition, Jamai-Osmania, Tarnaka, Hyderabad, Telangana, India Correspondence should be addressed to G. Bhanuprakash Reddy; geereddy@yahoo.com Received 23 October 2019; Revised 14 May 2020; Accepted 13 June 2020; Published 10 July 2020 Academic Editor: Barbara Shukitt-Hale Copyright © 2020 T. Shalini et al. -is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. -e purpose of this study was to assess the prevalence of frailty and nutritional status among older adults. -is population-based cross-sectional study was conducted in 163 subjects aged 60–88 years, from Hyderabad City, South India. Data were obtained on sociodemographic details and anthropometry and biochemical parameters. Dietary intake was assessed by a three-day 24 h dietary recall, and the probability of adequacy (PA) was calculated using the estimated average requirements. Frailty indicators were as follows: handgrip strength was measured by using a Jamar dynamometer, gait speed was measured by a ten-meter length walk test, and low physical activity level, weight loss, and exhaustion were assessed using a questionnaire. Among the study population, 20% of the participants were frail and 80% were nonfrail. -e prevalence of frailty is higher in older (30.1%) than the younger (12.2%) age groups, and it is more so in women (32.4%) than in men (10.1%). -e lower educational status and income were associated with frailty. -e PA of most of the nutrients was low in the frail group. Noticeably, the mean PA (MPA) across the fourteen micronutrients was signiﬁcantly higher in nonfrail (38%) compared to the frail group (25%). -e prevalence of frailty was higher in the lowest tertile of most of the food groups and nutrient intake compared to the highest tertile. -e study revealed a 20% prevalence of frailty among urban older adults and provided evidence that inadequate intake of nutrients is independently associated with frailty. hospitalization, dependence, and mortality, hence becoming 1. Introduction a major clinical and public health concern [3, 4]. -e average life span of humans at birth has been increased -ere are over 25 subjective and objective frailty as- in the last century, approximately from 45 years (the early sessment methods developed globally to assess frailty with 1900s) to 80 years today. It is estimated that by 2050, about many diﬀerent intangible deﬁnitions. -e most followed methods of measurement include the Rockwood frailty 21.5% (∼2 billion) of the global population will be over 60 years of age [1, 2]. -is demographic transition of increased index, which deﬁnes frailty as a result of several age-related life expectancy is associated with the burden of several age- deﬁcits that may lead to poor health [5]. -e second method related disorders, including frailty [3]. Frailty, a biologic or developed by Fried deﬁnes frailty as a unidimensional, geriatric syndrome characterized by multisystem dysregu- principally physical domain which includes three of ﬁve lation leading to a loss of dynamic homeostasis, decreased indicators such as exhaustion, weak grip strength, low en- physiological, functional, and cognitive reserves that confer ergy expenditure, slow walking speed, and weight loss [6]. vulnerability to adverse outcomes. Frail people are at a However, other researchers have proposed to include the higher risk of disability, falls, cognitive impairment, cognitive domain, a multidimensional construct, which 2 Journal of Aging Research could aid in a better understanding of the frailty phenotypes 2.2.DataCollection. Sociodemographic information such as and pathways to adverse outcomes [7]. age, literacy status, cohabitate details, food habits, and self- reported comorbid conditions was obtained using a ques- -e quality of life of aging people can be improved if tionnaire. Participants were categorized into two groups intervened at an early stage of functional decline by slowing, based on their food habits. -ose who never consumed delaying, or partly reversing the state of frailty, if assessed animal foods (such as poultry, meat, eggs, and ﬁsh) were appropriately [8]. Poor nutritional status is one of the factors included in the vegetarian group, and the others who found to be associated with frailty, which might be due to consumed both animal foods and plant foods were included insuﬃcient food intake. Epidemiological studies have re- in the mixed diet group. ported that dietary protein content, protein quality, and micronutrients could play a crucial role in the development and management of aging and frailty [9]. Moreover, ade- 2.2.1. Anthropometric Measurements. -e body weight and quate intakes of macronutrients and micronutrients have height were recorded using the SECA weighing scale and been found to reduce the risk of frailty [10]. anthropometric rod, respectively, and the body mass index (BMI) was calculated. Waist circumference (WC) was In developing countries such as India, frailty assessment measured using a ﬁber-reinforced nonelastic tape at a point among older adults has seldom received the attention of the midway between the lower rib region and the iliac crest, and investigators. Few studies reported varied prevalence hip circumference (HC) was measured by passing the tape (16.3–55.5%) of frailty in India [11–13], while some studies over maximum protuberance on buttocks. Asian cutoﬀ emphasized on physical, cognitive, and depression domains values were used for BMI classiﬁcation [16] and deﬁning separately [14, 15], but a comprehensive approach towards abdominal and central obesity [17]. Blood pressure (BP) was frailty assessment, particularly nutritional component, is measured thrice with a ﬁve-minute interval between each missing. -erefore, the present study was conducted (i) to measurement using a BP apparatus, and the average of three assess the prevalence of frailty among urban older adults readings was taken. Participants with systolic blood pressure using the Fried frailty phenotype criteria and (ii) to assess (SBP) of≥140 mmHg and diastolic blood pressure (DBP) of their nutritional status. ≥90 mmHg and/or those participants on antihypertensive medication were considered hypertensive [18]. 2. Methods 2.2.2. Biochemical Estimations. Fasting venous blood sam- 2.1. Study Design, Sample Size, and Recruitment of Subjects. ples were collected in heparin tubes early in the morning -is population-based cross-sectional study was conducted following overnight fast, and spot urine samples (ﬁrst- among older adults aged 60 years and above in the urban morning void) were collected in sterile urine containers. -e areas of Hyderabad Metro City, Telangana State, India, from samples were transported to the laboratory in the icebox for November 2016 to July 2017. Based on the reported prev- further analysis. Blood and plasma were separated by cen- alence of frailty among older adults as 56%, the sample size trifugation at 3500 rpm for 10 mins. Fasting blood glucose was calculated [11]. Assuming a 95% conﬁdence interval (FBG) was estimated in whole blood using an Accu-Chek (CI) with a relative precision of 20%, the sample size arrived Active glucometer [19]. Glycosylated haemoglobin (HbA1c) was 78. However, with a design eﬀect of 2, the sample size was estimated by an Aﬁnion AS100 Analyzer (Axis-Shield, comes to 156. Norway) based on the principle of boronate aﬃnity [20] and -e Hyderabad City was stratiﬁed into four zones (south, haemoglobin (Hb) by the cyanmethaemoglobin method east, west, and north), and two wards were selected from using a spectrophotometer (Shimadzu UV 2600). Lipid each zone by a simple random sampling procedure to proﬁle (high-density lipoprotein (HDL), total cholesterol capture the entire population of the city. To enroll partic- (TC), and triglycerides (TG)) was analyzed in plasma using ipants, health camps were organized at randomly selected commercially available kits from BioSystems (Barcelona, wards. From each ward, four locations were selected, and in Spain). Low-density lipoprotein (LDL) concentrations were each location, one health camp was organized. Approxi- calculated using the Friedewald formula [21]. Urinary al- mately, 20 subjects were approached in each health camp. bumin was quantiﬁed using a solid-phase immunochemical -e details of the selection and recruitment of the study assay and urinary creatinine by an enzymatic colourimetric participants are depicted in Figure 1. A total of 163 par- test in a fully automated Aﬁnion AS100 Analyzer (Axis- ticipants, 89 men and 74 women, who fulﬁlled the criteria Shield, Norway) [22], and then the urinary albumin-to- (mentioned in Figure 1) have consented for participation. creatinine ratio (UACR) (expressed as mg/g creatinine) was -e study was conducted according to the guidelines laid calculated. down in the 1964 Declaration of Helsinki and its later amendments. All procedures involving human participants were approved by the Institutional Ethics Committee 2.2.3. Cutoﬀs for Covariates. FBG< 110 mg/dL was con- (ethical approval number: IEC; # CR9/I/2014). Written sidered as normal, 110–125 mg/dL as impaired fasting informed consent (or thumb impression in the case of il- glucose (IFG), and ≥126 mg/dL as diabetic [23]. An HbA1c literates) was obtained from the participants who vol- value of< 6.5% was considered as normal [24]. -e preva- unteered to participate in the study. lence of anemia was calculated based on the Hb levels. Journal of Aging Research 3 587 elderly people aged 60 years and above volunteered to participate in the study Approached and were explained about the study design Subjects declined to participate in the diet survey (103) and blood sample collection (72) Screened 412 subjects were enrolled and screened for health status with a questionnaire 221 subjects were excluded due to the following: (i) Chronic alcohol abuse (45) (ii) Dementia, severe neurological or psychiatric illness (33) (iii) History of head trauma, inflammatory or infectious brain disease (24) (iv) Renal problems (52) (v) Antidepressant drugs usage for the past six months (58) (vi) Could not perform physical performance test (9) Enrolled 191 subjects were eligible after screening for health status (i) 23 subjects did not attend the blood and urine sampling (ii) 5 subjects with incomplete information were excluded Recruited 163 subjects (89 men and 74 women) were consented and sampled Figure 1: Flowchart showing the recruitment and selection of study participants. Anemia was deﬁned as a Hb value< 13.0 g/dL in men and nutrient value in the IFCT. After correction for moisture, the <12.0 g/dL in women [25]. -e optimal plasma concentra- nutritive values of these two databases were comparable tion of TC was<200 mg/dL,<130 mg/dL for LDL,<150 mg/ (within 10–20% variation). -e total daily consumption was dL for TG, and low HDL was ≥40 mg/dL in men and computed based on the above mentioned nutritive value ≥50 mg/dL in women [26]. According to the National databases and by taking the average of 3 days of diet survey, Kidney Foundation, UACR< 30 mg/g was considered as using the in-house software. normal, 30–300 mg/g as microalbuminuria, and ≥300 mg/g as overt nephropathy [27]. (1) Probability of Adequacy (PA). -e adequacy of micro- nutrients was assessed using the probability approach which relates an individual’s usual intake of nutrients to the dis- 2.2.4. Dietary Assessment. Individual dietary intake was tribution of requirements for a particular life stage and assessed in a subset of the samples (n � 88, 48 men and 40 gender group using estimated average requirement (EAR) women) using a systematic random sampling procedure. A values and its standard deviation (SD) [32–34]. -en, the PA 24 h dietary recall was carried out on three diﬀerent days (2 was computed using the “CDFNORM” function in SPSS nonconsecutive weekdays and one weekend day) to capture software. CDFNORM function is a cumulative probability intra- and interindividual variation [28]. -e member of the distribution of nutrient requirements, assumed to be a household who cooked food for the entire household was normal distribution, and is expressed as area under the interviewed for dietary intake of individuals during the probability curve. -is function computes by plotting each previous 24 h, excluding festival, function, and fasting days. individual’s intake data from the study population and A standardized set of twelve cups and two spoons were used constructs a risk curve using the requirement (EAR and SD) as visual tools for assessing portion sizes [29]. -e raw distribution of the group (Z score � (intake − EAR)/SD of the ingredients used for the food preparation were weighed requirement). -en, the risk curve was compared to the using a portable electronic digital diet scale (Seca Culina distribution of intakes of the study population to determine 852 ). -e quantities of raw foods were computed from the what proportion of the population has an inadequate intake. intakes of cooked foods (intakes of the raw food by the -us, PA determines the probability that an individual’s individual � (quantity of raw food in the preparation/total intake in a group meets the requirements, and then, their cooked quantity of food) × individual intake of cooked mean of the individual probabilities is obtained, which is food). used to estimate the prevalence of adequacy of a particular -e nutritive value of raw foods was calculated using the nutrient [34, 35]. Hence, the micronutrient adequacy was Indian Food-Composition Tables (IFCTs) [30], while the evaluated by calculating the PA for fourteen micronutrients United States Department of Agriculture Food and Nutrient that are of public health importance in this study: vitamins Database [31] was used for those foods that did not have a such as A, C, B1, B2, niacin, B6, folate, and B12, and minerals 4 Journal of Aging Research such as calcium, zinc, iron, magnesium, phosphorus, and On a scale of 5, a person who gets a score of 0–2 was selenium. -e recommended EAR, as set by the Institute of categorized as nonfrail and 3–5 score as a frail person [6, 40]. Medicine (IOM) (National Academies, Food and Nutrition Board) [36], according to the sex and age group, was 2.4.StatisticalAnalyses. Data analyses were performed using considered for the calculation of PA. -e resulting value for the SPSS software package (version 19.0, SPSS Inc, Chicago, PA ranged from 0 to 100%, and an overall mean PA (MPA) IL). As most of the data were skewed, the anthropometric was calculated by averaging the PA across the fourteen parameters, clinical variables, food groups, and nutrients by nutrients. -e prevalence of inadequacy was deﬁned by th frailty status were reported using medians and 25 (P ) and considering MPA below 50% (MPA< 0.5) [36, 37]. th 75 (P ) percentiles, and comparisons for the same were (2) Nutrient Density. Nutrient density is the ratio of the carried out by the Mann–Whitney U test. -e median values amount of nutrient intake in the diet to the energy provided of the variables (HGS and GS) were compared across the age by the same diet and is expressed as the amount of the groups and gender using a Kruskal–Wallis test with pair- nutrient per 1,000 kcal of energy [38]. wise-multiple comparisons. -e chi-square (χ ) test was used for testing the association between categorical vari- ables. Student’s t-test was used to compare the PA and MPA 2.3. Frailty Indicators. Five indicators were assessed to by frailty status. -e food groups and nutrients were divided measure frailty. -ese included (i) weakness, (ii) weight loss, into tertiles, and the associations between frailty status and (iii) physical activity level, (iv) exhaustion, and (v) gait speed the dietary variables were examined using the χ test. Sta- (GS). tistical signiﬁcance was considered at P< 0.05. 2.3.1. Weakness. Handgrip strength (HGS) was measured to 3. Results estimate the physical weakness of the participant using a Jamar hand-held dynamometer [6]. -e cutoﬀ for HGS -e median (P –P ) age of the participants was 65.0 25 75 stratiﬁed by gender and BMI is depicted in Supplementary (62.0–70.0) (Table 1). -e gender (men, 55%; women, 45%) Table 1A. To determine the cutoﬀ point for deﬁning the and the age-wise (60–65 years, 55%; ≥66 years, 45%) dis- th lowest quartile on measures of HGS, the 25 percentile was tributions were almost similar in both groups. -e majority used [39]. of the subjects were baccalaureate graduates and above (35.2%) and were consuming mixed diets (72%). About 3% of the subjects were underweight, 24% had a normal BMI, 2.3.2. Weight Loss. Self-reported unintentional weight loss and 73% were overweight and obese. was assessed in response to the question, “Have you lost any weight during the past 12 months?” -ose reporting a weight loss of 4.5 kg or more in the previous year were considered 3.1. Prevalence of Frailty and Its Association with Age and [6]. Gender. According to Fried frailty phenotype criteria, 20% of the study participants were frail and 80% were nonfrail (Figure 2(a)). We determined the association of two direct 2.3.3. Low Physical Activity Level. A question was asked to measures of frailty (HGS and GS) with age and gender. -e the participants, “Taking into account both work and leisure, HGS was observed to be lower with increasing age con- would you say that you are very, fairly, not very, or not at all sidering both genders, though it was not signiﬁcant. -e physically active?” -ose reported themselves as not very or HGS was signiﬁcantly higher in men compared to women in not at all physically active were considered physically in- both the age groups (Figure 2(b)). -ere was no diﬀerence in active [7]. GS between the age groups among men, but there was a diﬀerence between the age groups among women. -e GS of men was signiﬁcantly diﬀerent when compared to women of 2.3.4. Exhaustion. A question was asked to the participants, respective age groups (Figure 2(c)). “Are you feeling worn out or exhausted?” -e participants who reported themselves as exhausted were considered as exhausted [7]. 3.2. Nutritional Status of the Study Participants by Frailty Status. Median age and UACR were signiﬁcantly higher, 2.3.5. Gait Speed (GS). It was assessed by a standard timed whereas Hb was signiﬁcantly lower in the frail group compared to the nonfrail group. No signiﬁcant (P< 0.05) walking test in which a ﬁve-meter length of the string was laid along the ground, and the participants were asked to get diﬀerence was observed for other variables (Table 1). up from the chair and walk normally to the end of the string, -e prevalence of frailty in the ≥66-year age group turn round and walk back again, and sit on the chair [7]. Due (30.1%) was signiﬁcantly higher when compared to the to the change in stride length of a person, the GS varies with 60–65-year age group (12.2%). By gender, the prevalence of height. -e cutoﬀ for GS stratiﬁed by gender and height is frailty was signiﬁcantly higher in women (32.4%) than men depicted in Supplementary Table 1B. To determine the cutoﬀ (10.1%). Nonearning (41.5%) participants had a signiﬁcantly point for deﬁning the lowest quartile on measures of GS, the higher prevalence compared to earning (6.4%) participants. th 25 percentile was used [39]. Uneducated and participants of lower education had a Journal of Aging Research 5 Table 1: Comparison of anthropometric details and blood parameters between nonfrail and frail participants. Pooled (n � 163), Nonfrail (n � 130), Frail (n � 33), Parameter P value median (P –P ) median (P –P ) median (P –P ) 25 75 25 75 25 75 Age, years 65.0 (62.0–70.0) 64.0 (61.0–68.0) 70.0 (65.0–76.0) <0.001 Height, cm 160 (152–166) 161 (154–167) 155 (150–163) 0.032 Weight, kg 66.6 (58.6–73.7) 66.9 (59.2–73.7) 61.1 (49.0–72.3) 0.078 BMI, kg/m 25.7 (22.7–28.5) 26.0 (23.0–28.5) 24.3 (21.7–29.2) 0.243 WC, cm 94.0 (85.1–101.6) 94.0 (86.4–101.6) 91.4 (83.8–99.1) 0.329 HC, cm 99.1 (92.2–106.7) 99.1 (94.0–106.7) 98.3 (90.2–106.7) 0.709 WHR 0.95 (0.89–0.99) 0.95 (0.9–1.0) 0.93 (0.87–0.98) 0.214 SBP, mmHg 140.5 (130.0–162.0) 140.0 (128.0–160.0) 150.0 (134.0–171.0) 0.079 DBP, mmHg 83.0 (76.0–91.0) 81.0 (76.0–90.0) 85.0 (77.0–92.0) 0.634 FBG, mg/dl 110.0 (97.0–136.0) 108.5 (98.0–135.0) 112 (97.0–147.0) 0.705 TC, mg/dl 176.7 (144.2–208.0) 177.8 (148.2–209.6) 171.3 (139.3–198.8) 0.449 HDL, mg/dl 41.7 (33.4–49.3) 41.0 (33.0–48.9) 45.8 (34.7–50.3) 0.273 LDL, mg/dl 110.4 (83.1–141.0) 111.3 (84.0–145.5) 110.1 (76.0–128.7) 0.327 TG, mg/dl 101.7 (76.7–141.5) 103.4 (78.7–144.0) 96.1 (69.9–129.7) 0.451 Hb, g/dl 13.4 (12.4–14.6) 13.6 (12.6–14.7) 12.8 (11.9–13.6) 0.011 HbA1c, (%) 6.4 (5.8–7.4) 6.4 (5.8–7.4) 6.5 (6.0–7.7) 0.202 Creatinine, mg/dl 1.0 (0.9–1.1) 1.0 (0.9–1.1) 1.0 (0.9–1.1) 0.826 UACR, mg/g creatinine 15.1 (8.3–35.2) 13.4 (8.1–29.8) 24.6 (13.6–88.9) 0.009 BMI: body mass index; WC: waist circumference; WHR: waist-to-hip ratio; SBP: systolic blood pressure; DBP: diastolic blood pressure; FBG: fasting blood glucose; TC: total cholesterol; HDL: high-density lipoprotein cholesterol; LDL: low-density lipoprotein cholesterol; TG: triglycerides; Hb: haemoglobin; th th th HbA1c: glycosylated haemoglobin; UACR: urinary albumin-to-creatinine ratio; P : 25 percentile; P : 75 percentile. Values represent medians, 25 and 25 75 th 75 percentiles. P< 0.05 was considered to be signiﬁcant. signiﬁcantly higher prevalence of frailty compared to those weight were similar between frail and nonfrail groups who had higher education (Table 2). (Supplementary Table 2). -e median (P –P ) intakes of cereals and millets, 25 75 pulses and legumes, green leafy vegetables, roots and tubers, 3.5. Association of Food Groups and Nutrient Intake with nuts and oilseeds, spices and condiments, fruits, and fats and Frailty. Association of food groups and nutrient intake oils and all the nutrients except for vitamin B12 were sig- according to the tertiles in frail participants is shown in niﬁcantly lower in the frail group compared to the nonfrail Supplementary Tables 3A and 3B. Signiﬁcantly high prev- group (Table 3). Dietary energy intake, a proxy for food alence of frailty was observed in the lowest tertile intakes of intake, was signiﬁcantly low in the frail group. -e major most of the food groups and nutrients compared to the contributor to energy was carbohydrates (∼56%) and fat highest tertile. Model 1 (adjusted for age and gender) and (∼28%), and the protein intake was near to optimal (∼11%) model 2 (adjusted for age, gender, and energy) adjustments in both the groups (Table 3). did not result in any change in the existing associations. 4. Discussion 3.3. Probability of Adequacy by Frailty Status. -e PA of vitamin A (P � 0.038), vitamin C (P � 0.040), thiamine Proper nutrition plays an essential role in maintaining good (P � 0.001), folate (P � 0.013), vitamin B6 (P � 0.003), health. As nutritional status is an essential factor contrib- calcium (P � 0.013), zinc (P � 0.042), magnesium uting to frailty, inadequate food intake among older adults, (P< 0.001), phosphorus (P � 0.01), and selenium due to dentition problems, anorexia nervosa, social isolation, (P � 0.042) was signiﬁcantly lower in the frail group and economic hardships, makes them predisposed to frailty. compared to the nonfrail group (Figure 3). Noticeably, the If assessed beforehand, the process of frailty among older MPA across the fourteen micronutrients was 35% and was adults can be postponed, and hence, they may be provided signiﬁcantly higher in nonfrail (38%) compared to the frail with a healthy life. group (25%) (Figure 3). -e risk of micronutrient inade- Studies reported in India showed a varied prevalence quacy (MPA< 0.5) was about 84% in the study subjects and (16.3–55.5%) of frailty [11–13]. In the present study, the was associated with frailty status but not signiﬁcant prevalence of frailty was 20%. -is low-end prevalence of (P< 0.05) (Figure 4). -e prevalence of inadequacy frailty in this study may be due to age, ethnicity, and dietary (MPA< 0.5) was higher in the frail group (95%) compared to habits compared to the reported studies that were done in the nonfrail group (81%) (Figure 4). higher age groups (65 years). Physical inactivity results in loss of muscle mass due to the imbalance between synthesis and degradation of muscle 3.4. Food and Nutrient Quality of the Participants by Frailty proteins, even in healthy older adults. -is situation can Status. -e nutrient density and nutrients per kg body worsen owing to the steady loss of metabolic reserves and 6 Journal of Aging Research 100 60 AA 80% 20% Men Women Nonfrail Frail 60–65 years ≥66 years (a) (b) Men Women 60–65 years ≥66 years (c) Figure 2: Prevalence of frailty (a), the relation of handgrip strength (b), and gait speed (c) with age and gender. Signiﬁcant diﬀerences (P< 0.05) of median values with age and gender are indicated by diﬀerent superscript letters (A, B, and C) above the bars. functional capacity. Handgrip strength and GS were found frailty and disability increased with age and were higher in to be the predictors of physical functional status and all- women [11]. In a Cardiovascular Health Study (CHS) and SAGE study, education and income were found to be related cause mortality in older adults [41]. -is study has shown a trend in HGS reduction with increasing age, and men were to frailty [11, 42]. -e gender diﬀerence in frailty may be due stronger than women, in concurrence with the previous to lower lean mass, strength, diﬀerences in patterns of studies [39]. -is might be due to a decrease in the number physical activity and performance, longer life expectancy, and size of muscle ﬁbers with progressing age (type II) and and higher morbidity rates and more likely to live alone with the diﬀerence in dietary patterns (especially protein intake). the consequence of poor nutrition in women than men. A study reported that older adults in India had signiﬁcantly -e adequacy of most of the nutrients was low in the frail poor muscle strength than in the United States [14]. A cross- group, and the MPA across the fourteen micronutrients was sectional study among older North Indians revealed that the 25%. -e prevalence of frailty was observed to be higher in GS was found to be lower with increasing age and higher the lowest tertile of most of the nutrient intake and was with increasing height in both genders [39]. In agreement almost double compared to the highest tertile. -e associ- with this report, we have observed similar ﬁndings in the ations remained the same even after adjusted for model 1 present study. (age and gender) and model 2 (age, gender, and energy). -e ﬁndings of the current study concur with the recent Similarly, Health, Aging, and Body Composition (Health- studies that the prevalence of frailty increased with age, more ABC) study among community-dwelling older adults found so in women and participants having lower education and that low intake of dietary protein was associated with a 40% income [6, 11]. A Study on global AGEing and adult health loss of lean body mass [43] and the protein intake is the (SAGE) revealed that in low- and middle-countries, both primary factor responsible for muscle protein anabolism. Percentage (%) Gait speed (sec/10 meters) Handgrip strength (kg) Journal of Aging Research 7 Table 2: Association of sociodemographic details and anthropometry and blood parameters with frailty status. Parameter Pooled (n � 163) Nonfrail (n � 130) Frail (n � 33) P value Age, years 60–65 90 79 (87.8%) 11 (12.2%) 0.005 ≥66 73 51 (69.9%) 22 (30.1%) Gender Men 89 80 (89.9%) 9 (10.1%) <0.001 Women 74 50 (67.6%) 24 (32.4%) Food habits Vegetarian 45 32 (71.1%) 13 (28.8%) 0.426 Mixed diet 118 91 (77.1%) 27 (22.9%) Occupation Earning 47 44 (93.6%) 3 (6.4%) <0.001 Nonearning 41 24 (58.5%) 17 (41.5%) Education Uneducated 7 4 (57.1%) 3 (42.9%) 1–8 standard 20 9 (45.0%) 11 (55.0%) <0.001 9–12 standard 30 26 (86.7%) 4 (13.3%) Graduation and above 31 29 (93.5%) 2 (6.5%) BMI, kg/m <18.5 5 3 (60.0%) 2 (40.0%) 18.5–23 39 29 (74.4%) 10 (25.6%) 0.300 ≥23 119 98 (82.4%) 21 (17.6%) WC, cm Normal 29 20 (69.0%) 9 (31.0%) 0.279 Abdominal obesity 94 74 (78.7%) 20 (21.3%) WHR Normal 6 3 (50.0%) 3 (50.0%) 0.118 Central obesity 117 91 (77.8%) 26 (22.2%) Hypertension (HTN), mmHg Normal (SBP <140, DBP <90) 114 93 (81.6%) 21 (18.4%) 0.377 HTN (SBP ≥140, DBP ≥90) 49 37 (75.5%) 12 (24.5%) FBG, mg/dl <110 83 68 (81.9%) 15 (18.1%) 110–125 32 26 (81.3%) 6 (18.8%) 0.619 ≥126 48 36 (75.0%) 12 (25.0%) TC, mg/dl <200 113 88 (77.9%) 25 (22.1%) 0.370 ≥200 50 42 (84.0%) 8 (16.0%) TG, mg/dl <150 130 102 (78.5%) 28 (21.5%) 0.415 ≥150 33 28 (84.8%) 5 (15.2%) HDL, mg/dl Male: <40; female: <50 97 77 (79.4%) 20 (20.6%) 0.886 Male: ≥40; female: ≥50 66 53 (80.3%) 13 (19.7%) LDL, mg/dl <130 131 102 (77.9%) 29 (22.1%) 0.224 ≥130 32 28 (87.5%) 4 (12.5%) Hb, g/dl Male: <13; female: <12 30 23 (76.7%) 7 (23.3%) 0.497 Male: ≥13; female: ≥12 113 93 (82.3%) 20 (17.7%) HbA1c (%) <6.5 94 74 (78.7%) 20 (21.3%) 0.295 ≥6.5 69 55 (79.7%) 14 (20.3%) UACR, mg/g <30 77 63 (81.8%) 14 (18.2%) 30–300 29 18 (62.1%) 11 (37.9%) 0.097 ≥300 3 2 (66.7%) 1 (33.3%) Diabetes Yes 62 46 (74.2%) 16 (25.8%) 0.639 No 63 49 (77.8%) 14 (22.2%) 8 Journal of Aging Research Table 2: Continued. Parameter Pooled (n � 163) Nonfrail (n � 130) Frail (n � 33) P value Cataract Yes 37 26 (70.3%) 11 (29.7%) 0.277 No 87 69 (79.3%) 18 (20.7%) Osteoarthritis Yes 36 24 (66.7%) 12 (33.3%) 0.094 No 88 71 (80.7%) 17 (19.3%) BMI: body mass index; WC: waist circumference; WHR: waist-to-hip ratio; HTN: hypertension; SBP: systolic blood pressure; DBP: diastolic blood pressure; FBG: fasting blood glucose; TC: total cholesterol; HDL: high-density lipoprotein cholesterol; LDL: low-density lipoprotein cholesterol; TG: triglycerides; Hb: haemoglobin; HbA1c: glycosylated haemoglobin; UACR: urinary albumin-to-creatinine ratio. Values represent percentages (%). P< 0.05 was considered to be signiﬁcant. Table 3: Median (P –P ) intake of food groups and nutrients by frailty status. 25 75 Pooled (n � 88), Nonfrail (n � 68), Frail (n � 20), Food groups/nutrients P value median (P –P ) median (P –P ) median (P –P ) 25 75 25 75 25 75 Food groups Cereals and millets (g) 231.4 (205.2–277.9) 250.2 (208.7–289.6) 204.8 (188.0–227.9) 0.001 Pulses and legumes (g) 40.1 (25.4–47.5) 42.3 (32.2–51.5) 24.8 (17.9–36.5) <0.001 Green leafy vegetables (g) 17.1 (11.4–30.9) 18.0 (13.5–34.2) 11.9 (6.8–23.4) 0.014 Other vegetables (g) 130.9 (78.7–176.2) 131.8 (83.8–177.2) 110.9 (62.9–173.2) 0.504 Roots and tubers (g) 56.5 (42.4–79.7) 59.4 (46.1–84.1) 47.1 (33.7–60.1) 0.037 Nuts and oilseeds (g) 8.7 (4.6–13.6) 9.9 (5.2–14.2) 5.2 (3.8–8.2) 0.007 Spices and condiments (g) 10.4 (8.5–12.8) 11.3 (9.4–13.2) 7.7 (5.1–10.2) <0.001 Fruits (g) 113.2 (84.4–189.9) 124.5 (92.2–198.6) 100.8 (63.2–135.8) 0.019 Animal foods (g) 20.8 (0.0–52.6) 24.0 (0.0–58.5) 20.8 (0.0–52.6) 0.252 Milk and milk products (g or ml) 269.5 (217.7–342.2) 277.0 (227.7–349.9) 236.8 (183.0–318.8) 0.070 Fats and oils (g) 29.9 (22.5–35.6) 30.7 (25.4–36.8) 21.1 (16.3–29.0) 0.001 Sugar (g) 8.2 (5.0–11.7) 8.9 (5.0–12.3) 7.1 (4.8–10.0) 0.265 Nutrients Energy (kcal) 1902 (1625–2131) 1977 (1749–2155) 1484 (1317–1762) <0.001 Protein (g) 52.2 (43.7–57.1) 54.1 (48.6–59.5) 41.6 (34.8–49.3) <0.001 % of energy intake 10.9 10.9 10.9 Fat (g) 58.3 (50.6–66.0) 60.0 (53.4–70.5) 46.1 (35.2–58.6) <0.001 % of energy intake 28.1 28.4 27.2 Carbohydrates (g) 263.3 (232.0–299.7) 278.1 (238.1–310.0) 218.0 (197.7–250.0) <0.001 % of energy intake 56.4 56.0 57.8 Fiber (g) 28.9 (24.1–33.3) 30.3 (25.4–34.2) 21.0 (17.2–28.8) <0.001 Vitamin A (µg) 424.1 (290.1–646.0) 476.7 (323.2–680.4) 324.3 (210.7–439.0) 0.012 -iamine (mg) 1.03 (0.87–1.19) 1.07 (0.92–1.2) 0.8 (0.66–1.0) <0.001 Riboﬂavin (mg) 0.86 (0.71–1.02) 0.9 (0.75–1.0) 0.72 (0.63–0.83) 0.005 Niacin (mg) 8.4 (7.0–9.8) 8.8 (7.3–10.2) 6.6 (5.7–7.9) <0.001 Vitamin B6 (mg) 1.0 (0.85–1.2) 1.08 (0.9–1.24) 0.82 (0.68–0.92) <0.001 Folate (µg) 227.4 (186.3–274.6) 237.6 (198.2–280.7) 179.5 (146.5–226.3) 0.001 Vitamin B12 (µg) 0.54 (0.41–1.01) 0.55 (0.41–1.03) 0.5 (0.43–0.96) 0.984 Vitamin C (mg) 73.6 (55.2–92.0) 81.8 (57.6–96.3) 57.3 (37.5–74.6) 0.003 Calcium (mg) 590.3 (473.5–706.6) 623.7 (522.0–729.5) 482.8 (394.7–593.8) 0.002 Phosphorus (mg) 932.3 (776.4–1066.3) 969.6 (848.3–1079.7) 742.6 (613.2–875.3) <0.001 Iron (mg) 11.0 (8.7–12.6) 11.3 (9.8–13.1) 8.4 (5.9–11.1) <0.001 Zinc (mg) 6.8 (5.9–8.1) 7.2 (6.2–8.2) 5.4 (4.7–6.7) <0.001 Sodium (mg) 315.9 (268.5–381.1) 329.0 (290.9–389.7) 262.4 (217.1–294.3) <0.001 Potassium (mg) 1825.9 (1538.2–2222.7) 1899.5 (1619.3–2325.4) 1384.7 (1088.6–1647.5) <0.001 Selenium (µg) 36.0 (25.8–48.6) 38.9 (29.5–49.0) 24.4 (17.9–41.0) 0.013 P : 25th percentile; P : 75th percentile. Values represent medians, 25th and 75th percentiles, and are expressed per day. P< 0.05 was considered to be signiﬁcant. 25 75 Low intake of protein and vitamins D, E, C, and folate after function in muscles causes diminished energy production, which may lead to fatigue and weakness in frail individuals. adjusted for energy intake has been shown to be indepen- dently associated with frailty in the InCHIANTI study [10]. Likewise, in the present study, inadequate intakes by the frail Impairment of mitochondrial function is a hallmark of subjects as apparent by a higher prevalence of inadequacy frailty development [44], which may be inﬂuenced by the (MPA< 0.5) (95%) might aﬀect the mitochondrial function deﬁciency of micronutrients. -e depletion of mitochondrial in muscles which are in turn responsible for the increased Journal of Aging Research 9 A A relation was observed in the present study, wherein lower intakes of antioxidant vitamins (A and C) and minerals (zinc 80 and selenium) were associated with frailty. In conclusion, 20% of the study population was frail, the 60 risk of frailty increased with increasing age, and the women are predisposed more than men. -e signiﬁcant determi- 40 A nants associated with frailty were lower educational status B and income. Dietary intakes of food groups and the majority 20 A of nutrients were found to be low in frail participants. -e A A A A B A prevalence of inadequacy (MPA< 0.5) was about 95% in the B B frail group. -e ﬁndings of the study demonstrated that inadequate nutritional intake could be a contributing factor to frailty among older adults. Nonfrail 5. Strengths and Limitations Frail Pooled -is is the ﬁrst study in India that reports the prevalence of Figure 3: Probability of adequacy and mean probability of ade- frailty and its association with nutritional status among the quacy of micronutrients among nonfrail and frail participants. PA, urban older adults in South India. -ese ﬁndings contribute probability of adequacy; MPA, mean probability of adequacy. to the current knowledge of the prevalence of frailty and Pooled data represent the total number of samples (n � 88). Mean understanding its association with nutritional status. -e values between the groups were compared by Student’s t-test. Data diet calculations used in the study do not account for represent (%) adequacy, and signiﬁcant diﬀerences (P< 0.05) of mean values between the groups are indicated by diﬀerent su- cooking losses. -e results are based on the raw data analysis perscript letters (A and B) above the bars. and are independent of sampling weights and are not ad- justed for inﬂated SDs resulting from complex sampling design. -e present study population might not be a rep- resentation of the entire country concerning geography, X = 2.302, p = 0.129 food habits, and other cultural variations, which highlights the need for further studies with larger cohorts to sub- stantiate these ﬁndings. 60 Abbreviations 40 HGS: Handgrip strength GS: Gait speed BMI: Body mass index FBG: Fasting blood glucose UACR: Urinary albumin-to-creatinine ratio Nonfrail Frail Pooled PA: Probability of adequacy MPA: Mean probability of adequacy MPA < 0.5 EAR: Estimated average requirement. MPA ≥ 0.5 Figure 4: Association of the mean probability of adequacy (MPA) with frailty status. Data represent % inadequacy (<0.5) and % Data Availability adequacy (≥0.5) of micronutrients. Pooled data represent the total No data were used to support the ﬁndings of this study. number of samples (n � 88). P< 0.05 was considered to be signiﬁcant. Conflicts of Interest All authors declare that there are no conﬂicts of interest. physical inactivity in frail subjects. -ough the amount of food is low in the frail group, the quality of diet is almost equal in both groups as evidenced by nutrient density. Authors’ Contributions -e consumption of fruits and vegetables (rich in micronutrients, antioxidants, and ﬁber) was observed to be Conception and design were carried out by GBR and TS. low in frail older adults. A study demonstrated that the Data collection was performed by TS and PSC. Data in- consumption of three portions of fruits and two portions of terpretation and analysis were conducted by GBR, TS, GM, vegetables per day was related to a lower risk of frailty [45]. and BNK. Preparation of the manuscript was contributed by Another study reported an association between antioxidant TS and GBR. Primary responsibility of the ﬁnal content was deﬁciency and reduced muscle strength [10]. A similar taken by GBR. PA and MPA of micronutrients (%) Percentage of MPA Vitamin A Vitamin C iamine Riboﬂavin Niacin Vitamin B6 Folate Vitamin B12 Calcium Zinc Iron Magnesium Phosphorus Selenium MPA 10 Journal of Aging Research action on frailty-advantage JA,” European Journal of Internal Acknowledgments Medicine, vol. 56, pp. 26–32, 2018. [10] B. Bartali, E. A. Frongillo, S. Bandinelli et al., “Low nutrient TS acknowledges the research fellowship from the Indian intake is an essential component of frailty in older persons,” Council of Medical Research, Government of India. -e >e Journals of Gerontology Series A: Biological Sciences and authors are thankful to all the participants in the study. Medical Sciences, vol. 61, no. 6, pp. 589–593, 2006. -e authors sincerely thank Dr. AT Jotheeswaran, World [11] R. B. Biritwum, N. Minicuci, A. E. Yawson et al., “Prevalence Health Organization, Geneva, and Dr. Vivian Isaac, of and factors associated with frailty and disability in older Flinders Rural Health, South Australia, for constructive adults from China, Ghana, India, Mexico, Russia and South criticism and useful discussion in the preparation of the Africa,” Maturitas, vol. 91, pp. 8–18, 2016. manuscript. -e authors also acknowledge the help of Dr. [12] J. J. Llibre Rodriguez, A. M. Prina, D. Acosta et al., “-e S. Sreenivasa Reddy and Dr. M. 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Dave et al., “Objective measures of the frailty syndrome (hand grip strength and gait speed) and cardiovascular mortality: a systematic review,” International Journal of Cardiology, vol. 215, pp. 487–493, 2016. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Aging Research Hindawi Publishing Corporation http://www.deepdyve.com/lp/hindawi-publishing-corporation/frailty-and-nutritional-status-among-urban-older-adults-in-south-india-h8of9mzV73

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Publisher: Hindawi Publishing Corporation
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DOI: 10.1155/2020/8763413
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Abstract

Hindawi Journal of Aging Research Volume 2020, Article ID 8763413, 11 pages https://doi.org/10.1155/2020/8763413 Research Article Frailty and Nutritional Status among Urban Older Adults in South India 1 1 2 3 T. Shalini, P. Swathi Chitra, B. Naveen Kumar, G. Madhavi, and G. Bhanuprakash Reddy Department of Biochemistry, ICMR-National Institute of Nutrition, Jamai-Osmania, Tarnaka, Hyderabad, Telangana, India Department of Statistics, ICMR-National Institute of Nutrition, Jamai-Osmania, Tarnaka, Hyderabad, Telangana, India Department of Community Studies, ICMR-National Institute of Nutrition, Jamai-Osmania, Tarnaka, Hyderabad, Telangana, India Correspondence should be addressed to G. Bhanuprakash Reddy; geereddy@yahoo.com Received 23 October 2019; Revised 14 May 2020; Accepted 13 June 2020; Published 10 July 2020 Academic Editor: Barbara Shukitt-Hale Copyright © 2020 T. Shalini et al. -is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. -e purpose of this study was to assess the prevalence of frailty and nutritional status among older adults. -is population-based cross-sectional study was conducted in 163 subjects aged 60–88 years, from Hyderabad City, South India. Data were obtained on sociodemographic details and anthropometry and biochemical parameters. Dietary intake was assessed by a three-day 24 h dietary recall, and the probability of adequacy (PA) was calculated using the estimated average requirements. Frailty indicators were as follows: handgrip strength was measured by using a Jamar dynamometer, gait speed was measured by a ten-meter length walk test, and low physical activity level, weight loss, and exhaustion were assessed using a questionnaire. Among the study population, 20% of the participants were frail and 80% were nonfrail. -e prevalence of frailty is higher in older (30.1%) than the younger (12.2%) age groups, and it is more so in women (32.4%) than in men (10.1%). -e lower educational status and income were associated with frailty. -e PA of most of the nutrients was low in the frail group. Noticeably, the mean PA (MPA) across the fourteen micronutrients was signiﬁcantly higher in nonfrail (38%) compared to the frail group (25%). -e prevalence of frailty was higher in the lowest tertile of most of the food groups and nutrient intake compared to the highest tertile. -e study revealed a 20% prevalence of frailty among urban older adults and provided evidence that inadequate intake of nutrients is independently associated with frailty. hospitalization, dependence, and mortality, hence becoming 1. Introduction a major clinical and public health concern [3, 4]. -e average life span of humans at birth has been increased -ere are over 25 subjective and objective frailty as- in the last century, approximately from 45 years (the early sessment methods developed globally to assess frailty with 1900s) to 80 years today. It is estimated that by 2050, about many diﬀerent intangible deﬁnitions. -e most followed methods of measurement include the Rockwood frailty 21.5% (∼2 billion) of the global population will be over 60 years of age [1, 2]. -is demographic transition of increased index, which deﬁnes frailty as a result of several age-related life expectancy is associated with the burden of several age- deﬁcits that may lead to poor health [5]. -e second method related disorders, including frailty [3]. Frailty, a biologic or developed by Fried deﬁnes frailty as a unidimensional, geriatric syndrome characterized by multisystem dysregu- principally physical domain which includes three of ﬁve lation leading to a loss of dynamic homeostasis, decreased indicators such as exhaustion, weak grip strength, low en- physiological, functional, and cognitive reserves that confer ergy expenditure, slow walking speed, and weight loss [6]. vulnerability to adverse outcomes. Frail people are at a However, other researchers have proposed to include the higher risk of disability, falls, cognitive impairment, cognitive domain, a multidimensional construct, which 2 Journal of Aging Research could aid in a better understanding of the frailty phenotypes 2.2.DataCollection. Sociodemographic information such as and pathways to adverse outcomes [7]. age, literacy status, cohabitate details, food habits, and self- reported comorbid conditions was obtained using a ques- -e quality of life of aging people can be improved if tionnaire. Participants were categorized into two groups intervened at an early stage of functional decline by slowing, based on their food habits. -ose who never consumed delaying, or partly reversing the state of frailty, if assessed animal foods (such as poultry, meat, eggs, and ﬁsh) were appropriately [8]. Poor nutritional status is one of the factors included in the vegetarian group, and the others who found to be associated with frailty, which might be due to consumed both animal foods and plant foods were included insuﬃcient food intake. Epidemiological studies have re- in the mixed diet group. ported that dietary protein content, protein quality, and micronutrients could play a crucial role in the development and management of aging and frailty [9]. Moreover, ade- 2.2.1. Anthropometric Measurements. -e body weight and quate intakes of macronutrients and micronutrients have height were recorded using the SECA weighing scale and been found to reduce the risk of frailty [10]. anthropometric rod, respectively, and the body mass index (BMI) was calculated. Waist circumference (WC) was In developing countries such as India, frailty assessment measured using a ﬁber-reinforced nonelastic tape at a point among older adults has seldom received the attention of the midway between the lower rib region and the iliac crest, and investigators. Few studies reported varied prevalence hip circumference (HC) was measured by passing the tape (16.3–55.5%) of frailty in India [11–13], while some studies over maximum protuberance on buttocks. Asian cutoﬀ emphasized on physical, cognitive, and depression domains values were used for BMI classiﬁcation [16] and deﬁning separately [14, 15], but a comprehensive approach towards abdominal and central obesity [17]. Blood pressure (BP) was frailty assessment, particularly nutritional component, is measured thrice with a ﬁve-minute interval between each missing. -erefore, the present study was conducted (i) to measurement using a BP apparatus, and the average of three assess the prevalence of frailty among urban older adults readings was taken. Participants with systolic blood pressure using the Fried frailty phenotype criteria and (ii) to assess (SBP) of≥140 mmHg and diastolic blood pressure (DBP) of their nutritional status. ≥90 mmHg and/or those participants on antihypertensive medication were considered hypertensive [18]. 2. Methods 2.2.2. Biochemical Estimations. Fasting venous blood sam- 2.1. Study Design, Sample Size, and Recruitment of Subjects. ples were collected in heparin tubes early in the morning -is population-based cross-sectional study was conducted following overnight fast, and spot urine samples (ﬁrst- among older adults aged 60 years and above in the urban morning void) were collected in sterile urine containers. -e areas of Hyderabad Metro City, Telangana State, India, from samples were transported to the laboratory in the icebox for November 2016 to July 2017. Based on the reported prev- further analysis. Blood and plasma were separated by cen- alence of frailty among older adults as 56%, the sample size trifugation at 3500 rpm for 10 mins. Fasting blood glucose was calculated [11]. Assuming a 95% conﬁdence interval (FBG) was estimated in whole blood using an Accu-Chek (CI) with a relative precision of 20%, the sample size arrived Active glucometer [19]. Glycosylated haemoglobin (HbA1c) was 78. However, with a design eﬀect of 2, the sample size was estimated by an Aﬁnion AS100 Analyzer (Axis-Shield, comes to 156. Norway) based on the principle of boronate aﬃnity [20] and -e Hyderabad City was stratiﬁed into four zones (south, haemoglobin (Hb) by the cyanmethaemoglobin method east, west, and north), and two wards were selected from using a spectrophotometer (Shimadzu UV 2600). Lipid each zone by a simple random sampling procedure to proﬁle (high-density lipoprotein (HDL), total cholesterol capture the entire population of the city. To enroll partic- (TC), and triglycerides (TG)) was analyzed in plasma using ipants, health camps were organized at randomly selected commercially available kits from BioSystems (Barcelona, wards. From each ward, four locations were selected, and in Spain). Low-density lipoprotein (LDL) concentrations were each location, one health camp was organized. Approxi- calculated using the Friedewald formula [21]. Urinary al- mately, 20 subjects were approached in each health camp. bumin was quantiﬁed using a solid-phase immunochemical -e details of the selection and recruitment of the study assay and urinary creatinine by an enzymatic colourimetric participants are depicted in Figure 1. A total of 163 par- test in a fully automated Aﬁnion AS100 Analyzer (Axis- ticipants, 89 men and 74 women, who fulﬁlled the criteria Shield, Norway) [22], and then the urinary albumin-to- (mentioned in Figure 1) have consented for participation. creatinine ratio (UACR) (expressed as mg/g creatinine) was -e study was conducted according to the guidelines laid calculated. down in the 1964 Declaration of Helsinki and its later amendments. All procedures involving human participants were approved by the Institutional Ethics Committee 2.2.3. Cutoﬀs for Covariates. FBG< 110 mg/dL was con- (ethical approval number: IEC; # CR9/I/2014). Written sidered as normal, 110–125 mg/dL as impaired fasting informed consent (or thumb impression in the case of il- glucose (IFG), and ≥126 mg/dL as diabetic [23]. An HbA1c literates) was obtained from the participants who vol- value of< 6.5% was considered as normal [24]. -e preva- unteered to participate in the study. lence of anemia was calculated based on the Hb levels. Journal of Aging Research 3 587 elderly people aged 60 years and above volunteered to participate in the study Approached and were explained about the study design Subjects declined to participate in the diet survey (103) and blood sample collection (72) Screened 412 subjects were enrolled and screened for health status with a questionnaire 221 subjects were excluded due to the following: (i) Chronic alcohol abuse (45) (ii) Dementia, severe neurological or psychiatric illness (33) (iii) History of head trauma, inflammatory or infectious brain disease (24) (iv) Renal problems (52) (v) Antidepressant drugs usage for the past six months (58) (vi) Could not perform physical performance test (9) Enrolled 191 subjects were eligible after screening for health status (i) 23 subjects did not attend the blood and urine sampling (ii) 5 subjects with incomplete information were excluded Recruited 163 subjects (89 men and 74 women) were consented and sampled Figure 1: Flowchart showing the recruitment and selection of study participants. Anemia was deﬁned as a Hb value< 13.0 g/dL in men and nutrient value in the IFCT. After correction for moisture, the <12.0 g/dL in women [25]. -e optimal plasma concentra- nutritive values of these two databases were comparable tion of TC was<200 mg/dL,<130 mg/dL for LDL,<150 mg/ (within 10–20% variation). -e total daily consumption was dL for TG, and low HDL was ≥40 mg/dL in men and computed based on the above mentioned nutritive value ≥50 mg/dL in women [26]. According to the National databases and by taking the average of 3 days of diet survey, Kidney Foundation, UACR< 30 mg/g was considered as using the in-house software. normal, 30–300 mg/g as microalbuminuria, and ≥300 mg/g as overt nephropathy [27]. (1) Probability of Adequacy (PA). -e adequacy of micro- nutrients was assessed using the probability approach which relates an individual’s usual intake of nutrients to the dis- 2.2.4. Dietary Assessment. Individual dietary intake was tribution of requirements for a particular life stage and assessed in a subset of the samples (n � 88, 48 men and 40 gender group using estimated average requirement (EAR) women) using a systematic random sampling procedure. A values and its standard deviation (SD) [32–34]. -en, the PA 24 h dietary recall was carried out on three diﬀerent days (2 was computed using the “CDFNORM” function in SPSS nonconsecutive weekdays and one weekend day) to capture software. CDFNORM function is a cumulative probability intra- and interindividual variation [28]. -e member of the distribution of nutrient requirements, assumed to be a household who cooked food for the entire household was normal distribution, and is expressed as area under the interviewed for dietary intake of individuals during the probability curve. -is function computes by plotting each previous 24 h, excluding festival, function, and fasting days. individual’s intake data from the study population and A standardized set of twelve cups and two spoons were used constructs a risk curve using the requirement (EAR and SD) as visual tools for assessing portion sizes [29]. -e raw distribution of the group (Z score � (intake − EAR)/SD of the ingredients used for the food preparation were weighed requirement). -en, the risk curve was compared to the using a portable electronic digital diet scale (Seca Culina distribution of intakes of the study population to determine 852 ). -e quantities of raw foods were computed from the what proportion of the population has an inadequate intake. intakes of cooked foods (intakes of the raw food by the -us, PA determines the probability that an individual’s individual � (quantity of raw food in the preparation/total intake in a group meets the requirements, and then, their cooked quantity of food) × individual intake of cooked mean of the individual probabilities is obtained, which is food). used to estimate the prevalence of adequacy of a particular -e nutritive value of raw foods was calculated using the nutrient [34, 35]. Hence, the micronutrient adequacy was Indian Food-Composition Tables (IFCTs) [30], while the evaluated by calculating the PA for fourteen micronutrients United States Department of Agriculture Food and Nutrient that are of public health importance in this study: vitamins Database [31] was used for those foods that did not have a such as A, C, B1, B2, niacin, B6, folate, and B12, and minerals 4 Journal of Aging Research such as calcium, zinc, iron, magnesium, phosphorus, and On a scale of 5, a person who gets a score of 0–2 was selenium. -e recommended EAR, as set by the Institute of categorized as nonfrail and 3–5 score as a frail person [6, 40]. Medicine (IOM) (National Academies, Food and Nutrition Board) [36], according to the sex and age group, was 2.4.StatisticalAnalyses. Data analyses were performed using considered for the calculation of PA. -e resulting value for the SPSS software package (version 19.0, SPSS Inc, Chicago, PA ranged from 0 to 100%, and an overall mean PA (MPA) IL). As most of the data were skewed, the anthropometric was calculated by averaging the PA across the fourteen parameters, clinical variables, food groups, and nutrients by nutrients. -e prevalence of inadequacy was deﬁned by th frailty status were reported using medians and 25 (P ) and considering MPA below 50% (MPA< 0.5) [36, 37]. th 75 (P ) percentiles, and comparisons for the same were (2) Nutrient Density. Nutrient density is the ratio of the carried out by the Mann–Whitney U test. -e median values amount of nutrient intake in the diet to the energy provided of the variables (HGS and GS) were compared across the age by the same diet and is expressed as the amount of the groups and gender using a Kruskal–Wallis test with pair- nutrient per 1,000 kcal of energy [38]. wise-multiple comparisons. -e chi-square (χ ) test was used for testing the association between categorical vari- ables. Student’s t-test was used to compare the PA and MPA 2.3. Frailty Indicators. Five indicators were assessed to by frailty status. -e food groups and nutrients were divided measure frailty. -ese included (i) weakness, (ii) weight loss, into tertiles, and the associations between frailty status and (iii) physical activity level, (iv) exhaustion, and (v) gait speed the dietary variables were examined using the χ test. Sta- (GS). tistical signiﬁcance was considered at P< 0.05. 2.3.1. Weakness. Handgrip strength (HGS) was measured to 3. Results estimate the physical weakness of the participant using a Jamar hand-held dynamometer [6]. -e cutoﬀ for HGS -e median (P –P ) age of the participants was 65.0 25 75 stratiﬁed by gender and BMI is depicted in Supplementary (62.0–70.0) (Table 1). -e gender (men, 55%; women, 45%) Table 1A. To determine the cutoﬀ point for deﬁning the and the age-wise (60–65 years, 55%; ≥66 years, 45%) dis- th lowest quartile on measures of HGS, the 25 percentile was tributions were almost similar in both groups. -e majority used [39]. of the subjects were baccalaureate graduates and above (35.2%) and were consuming mixed diets (72%). About 3% of the subjects were underweight, 24% had a normal BMI, 2.3.2. Weight Loss. Self-reported unintentional weight loss and 73% were overweight and obese. was assessed in response to the question, “Have you lost any weight during the past 12 months?” -ose reporting a weight loss of 4.5 kg or more in the previous year were considered 3.1. Prevalence of Frailty and Its Association with Age and [6]. Gender. According to Fried frailty phenotype criteria, 20% of the study participants were frail and 80% were nonfrail (Figure 2(a)). We determined the association of two direct 2.3.3. Low Physical Activity Level. A question was asked to measures of frailty (HGS and GS) with age and gender. -e the participants, “Taking into account both work and leisure, HGS was observed to be lower with increasing age con- would you say that you are very, fairly, not very, or not at all sidering both genders, though it was not signiﬁcant. -e physically active?” -ose reported themselves as not very or HGS was signiﬁcantly higher in men compared to women in not at all physically active were considered physically in- both the age groups (Figure 2(b)). -ere was no diﬀerence in active [7]. GS between the age groups among men, but there was a diﬀerence between the age groups among women. -e GS of men was signiﬁcantly diﬀerent when compared to women of 2.3.4. Exhaustion. A question was asked to the participants, respective age groups (Figure 2(c)). “Are you feeling worn out or exhausted?” -e participants who reported themselves as exhausted were considered as exhausted [7]. 3.2. Nutritional Status of the Study Participants by Frailty Status. Median age and UACR were signiﬁcantly higher, 2.3.5. Gait Speed (GS). It was assessed by a standard timed whereas Hb was signiﬁcantly lower in the frail group compared to the nonfrail group. No signiﬁcant (P< 0.05) walking test in which a ﬁve-meter length of the string was laid along the ground, and the participants were asked to get diﬀerence was observed for other variables (Table 1). up from the chair and walk normally to the end of the string, -e prevalence of frailty in the ≥66-year age group turn round and walk back again, and sit on the chair [7]. Due (30.1%) was signiﬁcantly higher when compared to the to the change in stride length of a person, the GS varies with 60–65-year age group (12.2%). By gender, the prevalence of height. -e cutoﬀ for GS stratiﬁed by gender and height is frailty was signiﬁcantly higher in women (32.4%) than men depicted in Supplementary Table 1B. To determine the cutoﬀ (10.1%). Nonearning (41.5%) participants had a signiﬁcantly point for deﬁning the lowest quartile on measures of GS, the higher prevalence compared to earning (6.4%) participants. th 25 percentile was used [39]. Uneducated and participants of lower education had a Journal of Aging Research 5 Table 1: Comparison of anthropometric details and blood parameters between nonfrail and frail participants. Pooled (n � 163), Nonfrail (n � 130), Frail (n � 33), Parameter P value median (P –P ) median (P –P ) median (P –P ) 25 75 25 75 25 75 Age, years 65.0 (62.0–70.0) 64.0 (61.0–68.0) 70.0 (65.0–76.0) <0.001 Height, cm 160 (152–166) 161 (154–167) 155 (150–163) 0.032 Weight, kg 66.6 (58.6–73.7) 66.9 (59.2–73.7) 61.1 (49.0–72.3) 0.078 BMI, kg/m 25.7 (22.7–28.5) 26.0 (23.0–28.5) 24.3 (21.7–29.2) 0.243 WC, cm 94.0 (85.1–101.6) 94.0 (86.4–101.6) 91.4 (83.8–99.1) 0.329 HC, cm 99.1 (92.2–106.7) 99.1 (94.0–106.7) 98.3 (90.2–106.7) 0.709 WHR 0.95 (0.89–0.99) 0.95 (0.9–1.0) 0.93 (0.87–0.98) 0.214 SBP, mmHg 140.5 (130.0–162.0) 140.0 (128.0–160.0) 150.0 (134.0–171.0) 0.079 DBP, mmHg 83.0 (76.0–91.0) 81.0 (76.0–90.0) 85.0 (77.0–92.0) 0.634 FBG, mg/dl 110.0 (97.0–136.0) 108.5 (98.0–135.0) 112 (97.0–147.0) 0.705 TC, mg/dl 176.7 (144.2–208.0) 177.8 (148.2–209.6) 171.3 (139.3–198.8) 0.449 HDL, mg/dl 41.7 (33.4–49.3) 41.0 (33.0–48.9) 45.8 (34.7–50.3) 0.273 LDL, mg/dl 110.4 (83.1–141.0) 111.3 (84.0–145.5) 110.1 (76.0–128.7) 0.327 TG, mg/dl 101.7 (76.7–141.5) 103.4 (78.7–144.0) 96.1 (69.9–129.7) 0.451 Hb, g/dl 13.4 (12.4–14.6) 13.6 (12.6–14.7) 12.8 (11.9–13.6) 0.011 HbA1c, (%) 6.4 (5.8–7.4) 6.4 (5.8–7.4) 6.5 (6.0–7.7) 0.202 Creatinine, mg/dl 1.0 (0.9–1.1) 1.0 (0.9–1.1) 1.0 (0.9–1.1) 0.826 UACR, mg/g creatinine 15.1 (8.3–35.2) 13.4 (8.1–29.8) 24.6 (13.6–88.9) 0.009 BMI: body mass index; WC: waist circumference; WHR: waist-to-hip ratio; SBP: systolic blood pressure; DBP: diastolic blood pressure; FBG: fasting blood glucose; TC: total cholesterol; HDL: high-density lipoprotein cholesterol; LDL: low-density lipoprotein cholesterol; TG: triglycerides; Hb: haemoglobin; th th th HbA1c: glycosylated haemoglobin; UACR: urinary albumin-to-creatinine ratio; P : 25 percentile; P : 75 percentile. Values represent medians, 25 and 25 75 th 75 percentiles. P< 0.05 was considered to be signiﬁcant. signiﬁcantly higher prevalence of frailty compared to those weight were similar between frail and nonfrail groups who had higher education (Table 2). (Supplementary Table 2). -e median (P –P ) intakes of cereals and millets, 25 75 pulses and legumes, green leafy vegetables, roots and tubers, 3.5. Association of Food Groups and Nutrient Intake with nuts and oilseeds, spices and condiments, fruits, and fats and Frailty. Association of food groups and nutrient intake oils and all the nutrients except for vitamin B12 were sig- according to the tertiles in frail participants is shown in niﬁcantly lower in the frail group compared to the nonfrail Supplementary Tables 3A and 3B. Signiﬁcantly high prev- group (Table 3). Dietary energy intake, a proxy for food alence of frailty was observed in the lowest tertile intakes of intake, was signiﬁcantly low in the frail group. -e major most of the food groups and nutrients compared to the contributor to energy was carbohydrates (∼56%) and fat highest tertile. Model 1 (adjusted for age and gender) and (∼28%), and the protein intake was near to optimal (∼11%) model 2 (adjusted for age, gender, and energy) adjustments in both the groups (Table 3). did not result in any change in the existing associations. 4. Discussion 3.3. Probability of Adequacy by Frailty Status. -e PA of vitamin A (P � 0.038), vitamin C (P � 0.040), thiamine Proper nutrition plays an essential role in maintaining good (P � 0.001), folate (P � 0.013), vitamin B6 (P � 0.003), health. As nutritional status is an essential factor contrib- calcium (P � 0.013), zinc (P � 0.042), magnesium uting to frailty, inadequate food intake among older adults, (P< 0.001), phosphorus (P � 0.01), and selenium due to dentition problems, anorexia nervosa, social isolation, (P � 0.042) was signiﬁcantly lower in the frail group and economic hardships, makes them predisposed to frailty. compared to the nonfrail group (Figure 3). Noticeably, the If assessed beforehand, the process of frailty among older MPA across the fourteen micronutrients was 35% and was adults can be postponed, and hence, they may be provided signiﬁcantly higher in nonfrail (38%) compared to the frail with a healthy life. group (25%) (Figure 3). -e risk of micronutrient inade- Studies reported in India showed a varied prevalence quacy (MPA< 0.5) was about 84% in the study subjects and (16.3–55.5%) of frailty [11–13]. In the present study, the was associated with frailty status but not signiﬁcant prevalence of frailty was 20%. -is low-end prevalence of (P< 0.05) (Figure 4). -e prevalence of inadequacy frailty in this study may be due to age, ethnicity, and dietary (MPA< 0.5) was higher in the frail group (95%) compared to habits compared to the reported studies that were done in the nonfrail group (81%) (Figure 4). higher age groups (65 years). Physical inactivity results in loss of muscle mass due to the imbalance between synthesis and degradation of muscle 3.4. Food and Nutrient Quality of the Participants by Frailty proteins, even in healthy older adults. -is situation can Status. -e nutrient density and nutrients per kg body worsen owing to the steady loss of metabolic reserves and 6 Journal of Aging Research 100 60 AA 80% 20% Men Women Nonfrail Frail 60–65 years ≥66 years (a) (b) Men Women 60–65 years ≥66 years (c) Figure 2: Prevalence of frailty (a), the relation of handgrip strength (b), and gait speed (c) with age and gender. Signiﬁcant diﬀerences (P< 0.05) of median values with age and gender are indicated by diﬀerent superscript letters (A, B, and C) above the bars. functional capacity. Handgrip strength and GS were found frailty and disability increased with age and were higher in to be the predictors of physical functional status and all- women [11]. In a Cardiovascular Health Study (CHS) and SAGE study, education and income were found to be related cause mortality in older adults [41]. -is study has shown a trend in HGS reduction with increasing age, and men were to frailty [11, 42]. -e gender diﬀerence in frailty may be due stronger than women, in concurrence with the previous to lower lean mass, strength, diﬀerences in patterns of studies [39]. -is might be due to a decrease in the number physical activity and performance, longer life expectancy, and size of muscle ﬁbers with progressing age (type II) and and higher morbidity rates and more likely to live alone with the diﬀerence in dietary patterns (especially protein intake). the consequence of poor nutrition in women than men. A study reported that older adults in India had signiﬁcantly -e adequacy of most of the nutrients was low in the frail poor muscle strength than in the United States [14]. A cross- group, and the MPA across the fourteen micronutrients was sectional study among older North Indians revealed that the 25%. -e prevalence of frailty was observed to be higher in GS was found to be lower with increasing age and higher the lowest tertile of most of the nutrient intake and was with increasing height in both genders [39]. In agreement almost double compared to the highest tertile. -e associ- with this report, we have observed similar ﬁndings in the ations remained the same even after adjusted for model 1 present study. (age and gender) and model 2 (age, gender, and energy). -e ﬁndings of the current study concur with the recent Similarly, Health, Aging, and Body Composition (Health- studies that the prevalence of frailty increased with age, more ABC) study among community-dwelling older adults found so in women and participants having lower education and that low intake of dietary protein was associated with a 40% income [6, 11]. A Study on global AGEing and adult health loss of lean body mass [43] and the protein intake is the (SAGE) revealed that in low- and middle-countries, both primary factor responsible for muscle protein anabolism. Percentage (%) Gait speed (sec/10 meters) Handgrip strength (kg) Journal of Aging Research 7 Table 2: Association of sociodemographic details and anthropometry and blood parameters with frailty status. Parameter Pooled (n � 163) Nonfrail (n � 130) Frail (n � 33) P value Age, years 60–65 90 79 (87.8%) 11 (12.2%) 0.005 ≥66 73 51 (69.9%) 22 (30.1%) Gender Men 89 80 (89.9%) 9 (10.1%) <0.001 Women 74 50 (67.6%) 24 (32.4%) Food habits Vegetarian 45 32 (71.1%) 13 (28.8%) 0.426 Mixed diet 118 91 (77.1%) 27 (22.9%) Occupation Earning 47 44 (93.6%) 3 (6.4%) <0.001 Nonearning 41 24 (58.5%) 17 (41.5%) Education Uneducated 7 4 (57.1%) 3 (42.9%) 1–8 standard 20 9 (45.0%) 11 (55.0%) <0.001 9–12 standard 30 26 (86.7%) 4 (13.3%) Graduation and above 31 29 (93.5%) 2 (6.5%) BMI, kg/m <18.5 5 3 (60.0%) 2 (40.0%) 18.5–23 39 29 (74.4%) 10 (25.6%) 0.300 ≥23 119 98 (82.4%) 21 (17.6%) WC, cm Normal 29 20 (69.0%) 9 (31.0%) 0.279 Abdominal obesity 94 74 (78.7%) 20 (21.3%) WHR Normal 6 3 (50.0%) 3 (50.0%) 0.118 Central obesity 117 91 (77.8%) 26 (22.2%) Hypertension (HTN), mmHg Normal (SBP <140, DBP <90) 114 93 (81.6%) 21 (18.4%) 0.377 HTN (SBP ≥140, DBP ≥90) 49 37 (75.5%) 12 (24.5%) FBG, mg/dl <110 83 68 (81.9%) 15 (18.1%) 110–125 32 26 (81.3%) 6 (18.8%) 0.619 ≥126 48 36 (75.0%) 12 (25.0%) TC, mg/dl <200 113 88 (77.9%) 25 (22.1%) 0.370 ≥200 50 42 (84.0%) 8 (16.0%) TG, mg/dl <150 130 102 (78.5%) 28 (21.5%) 0.415 ≥150 33 28 (84.8%) 5 (15.2%) HDL, mg/dl Male: <40; female: <50 97 77 (79.4%) 20 (20.6%) 0.886 Male: ≥40; female: ≥50 66 53 (80.3%) 13 (19.7%) LDL, mg/dl <130 131 102 (77.9%) 29 (22.1%) 0.224 ≥130 32 28 (87.5%) 4 (12.5%) Hb, g/dl Male: <13; female: <12 30 23 (76.7%) 7 (23.3%) 0.497 Male: ≥13; female: ≥12 113 93 (82.3%) 20 (17.7%) HbA1c (%) <6.5 94 74 (78.7%) 20 (21.3%) 0.295 ≥6.5 69 55 (79.7%) 14 (20.3%) UACR, mg/g <30 77 63 (81.8%) 14 (18.2%) 30–300 29 18 (62.1%) 11 (37.9%) 0.097 ≥300 3 2 (66.7%) 1 (33.3%) Diabetes Yes 62 46 (74.2%) 16 (25.8%) 0.639 No 63 49 (77.8%) 14 (22.2%) 8 Journal of Aging Research Table 2: Continued. Parameter Pooled (n � 163) Nonfrail (n � 130) Frail (n � 33) P value Cataract Yes 37 26 (70.3%) 11 (29.7%) 0.277 No 87 69 (79.3%) 18 (20.7%) Osteoarthritis Yes 36 24 (66.7%) 12 (33.3%) 0.094 No 88 71 (80.7%) 17 (19.3%) BMI: body mass index; WC: waist circumference; WHR: waist-to-hip ratio; HTN: hypertension; SBP: systolic blood pressure; DBP: diastolic blood pressure; FBG: fasting blood glucose; TC: total cholesterol; HDL: high-density lipoprotein cholesterol; LDL: low-density lipoprotein cholesterol; TG: triglycerides; Hb: haemoglobin; HbA1c: glycosylated haemoglobin; UACR: urinary albumin-to-creatinine ratio. Values represent percentages (%). P< 0.05 was considered to be signiﬁcant. Table 3: Median (P –P ) intake of food groups and nutrients by frailty status. 25 75 Pooled (n � 88), Nonfrail (n � 68), Frail (n � 20), Food groups/nutrients P value median (P –P ) median (P –P ) median (P –P ) 25 75 25 75 25 75 Food groups Cereals and millets (g) 231.4 (205.2–277.9) 250.2 (208.7–289.6) 204.8 (188.0–227.9) 0.001 Pulses and legumes (g) 40.1 (25.4–47.5) 42.3 (32.2–51.5) 24.8 (17.9–36.5) <0.001 Green leafy vegetables (g) 17.1 (11.4–30.9) 18.0 (13.5–34.2) 11.9 (6.8–23.4) 0.014 Other vegetables (g) 130.9 (78.7–176.2) 131.8 (83.8–177.2) 110.9 (62.9–173.2) 0.504 Roots and tubers (g) 56.5 (42.4–79.7) 59.4 (46.1–84.1) 47.1 (33.7–60.1) 0.037 Nuts and oilseeds (g) 8.7 (4.6–13.6) 9.9 (5.2–14.2) 5.2 (3.8–8.2) 0.007 Spices and condiments (g) 10.4 (8.5–12.8) 11.3 (9.4–13.2) 7.7 (5.1–10.2) <0.001 Fruits (g) 113.2 (84.4–189.9) 124.5 (92.2–198.6) 100.8 (63.2–135.8) 0.019 Animal foods (g) 20.8 (0.0–52.6) 24.0 (0.0–58.5) 20.8 (0.0–52.6) 0.252 Milk and milk products (g or ml) 269.5 (217.7–342.2) 277.0 (227.7–349.9) 236.8 (183.0–318.8) 0.070 Fats and oils (g) 29.9 (22.5–35.6) 30.7 (25.4–36.8) 21.1 (16.3–29.0) 0.001 Sugar (g) 8.2 (5.0–11.7) 8.9 (5.0–12.3) 7.1 (4.8–10.0) 0.265 Nutrients Energy (kcal) 1902 (1625–2131) 1977 (1749–2155) 1484 (1317–1762) <0.001 Protein (g) 52.2 (43.7–57.1) 54.1 (48.6–59.5) 41.6 (34.8–49.3) <0.001 % of energy intake 10.9 10.9 10.9 Fat (g) 58.3 (50.6–66.0) 60.0 (53.4–70.5) 46.1 (35.2–58.6) <0.001 % of energy intake 28.1 28.4 27.2 Carbohydrates (g) 263.3 (232.0–299.7) 278.1 (238.1–310.0) 218.0 (197.7–250.0) <0.001 % of energy intake 56.4 56.0 57.8 Fiber (g) 28.9 (24.1–33.3) 30.3 (25.4–34.2) 21.0 (17.2–28.8) <0.001 Vitamin A (µg) 424.1 (290.1–646.0) 476.7 (323.2–680.4) 324.3 (210.7–439.0) 0.012 -iamine (mg) 1.03 (0.87–1.19) 1.07 (0.92–1.2) 0.8 (0.66–1.0) <0.001 Riboﬂavin (mg) 0.86 (0.71–1.02) 0.9 (0.75–1.0) 0.72 (0.63–0.83) 0.005 Niacin (mg) 8.4 (7.0–9.8) 8.8 (7.3–10.2) 6.6 (5.7–7.9) <0.001 Vitamin B6 (mg) 1.0 (0.85–1.2) 1.08 (0.9–1.24) 0.82 (0.68–0.92) <0.001 Folate (µg) 227.4 (186.3–274.6) 237.6 (198.2–280.7) 179.5 (146.5–226.3) 0.001 Vitamin B12 (µg) 0.54 (0.41–1.01) 0.55 (0.41–1.03) 0.5 (0.43–0.96) 0.984 Vitamin C (mg) 73.6 (55.2–92.0) 81.8 (57.6–96.3) 57.3 (37.5–74.6) 0.003 Calcium (mg) 590.3 (473.5–706.6) 623.7 (522.0–729.5) 482.8 (394.7–593.8) 0.002 Phosphorus (mg) 932.3 (776.4–1066.3) 969.6 (848.3–1079.7) 742.6 (613.2–875.3) <0.001 Iron (mg) 11.0 (8.7–12.6) 11.3 (9.8–13.1) 8.4 (5.9–11.1) <0.001 Zinc (mg) 6.8 (5.9–8.1) 7.2 (6.2–8.2) 5.4 (4.7–6.7) <0.001 Sodium (mg) 315.9 (268.5–381.1) 329.0 (290.9–389.7) 262.4 (217.1–294.3) <0.001 Potassium (mg) 1825.9 (1538.2–2222.7) 1899.5 (1619.3–2325.4) 1384.7 (1088.6–1647.5) <0.001 Selenium (µg) 36.0 (25.8–48.6) 38.9 (29.5–49.0) 24.4 (17.9–41.0) 0.013 P : 25th percentile; P : 75th percentile. Values represent medians, 25th and 75th percentiles, and are expressed per day. P< 0.05 was considered to be signiﬁcant. 25 75 Low intake of protein and vitamins D, E, C, and folate after function in muscles causes diminished energy production, which may lead to fatigue and weakness in frail individuals. adjusted for energy intake has been shown to be indepen- dently associated with frailty in the InCHIANTI study [10]. Likewise, in the present study, inadequate intakes by the frail Impairment of mitochondrial function is a hallmark of subjects as apparent by a higher prevalence of inadequacy frailty development [44], which may be inﬂuenced by the (MPA< 0.5) (95%) might aﬀect the mitochondrial function deﬁciency of micronutrients. -e depletion of mitochondrial in muscles which are in turn responsible for the increased Journal of Aging Research 9 A A relation was observed in the present study, wherein lower intakes of antioxidant vitamins (A and C) and minerals (zinc 80 and selenium) were associated with frailty. In conclusion, 20% of the study population was frail, the 60 risk of frailty increased with increasing age, and the women are predisposed more than men. -e signiﬁcant determi- 40 A nants associated with frailty were lower educational status B and income. Dietary intakes of food groups and the majority 20 A of nutrients were found to be low in frail participants. -e A A A A B A prevalence of inadequacy (MPA< 0.5) was about 95% in the B B frail group. -e ﬁndings of the study demonstrated that inadequate nutritional intake could be a contributing factor to frailty among older adults. Nonfrail 5. Strengths and Limitations Frail Pooled -is is the ﬁrst study in India that reports the prevalence of Figure 3: Probability of adequacy and mean probability of ade- frailty and its association with nutritional status among the quacy of micronutrients among nonfrail and frail participants. PA, urban older adults in South India. -ese ﬁndings contribute probability of adequacy; MPA, mean probability of adequacy. to the current knowledge of the prevalence of frailty and Pooled data represent the total number of samples (n � 88). Mean understanding its association with nutritional status. -e values between the groups were compared by Student’s t-test. Data diet calculations used in the study do not account for represent (%) adequacy, and signiﬁcant diﬀerences (P< 0.05) of mean values between the groups are indicated by diﬀerent su- cooking losses. -e results are based on the raw data analysis perscript letters (A and B) above the bars. and are independent of sampling weights and are not ad- justed for inﬂated SDs resulting from complex sampling design. -e present study population might not be a rep- resentation of the entire country concerning geography, X = 2.302, p = 0.129 food habits, and other cultural variations, which highlights the need for further studies with larger cohorts to sub- stantiate these ﬁndings. 60 Abbreviations 40 HGS: Handgrip strength GS: Gait speed BMI: Body mass index FBG: Fasting blood glucose UACR: Urinary albumin-to-creatinine ratio Nonfrail Frail Pooled PA: Probability of adequacy MPA: Mean probability of adequacy MPA < 0.5 EAR: Estimated average requirement. MPA ≥ 0.5 Figure 4: Association of the mean probability of adequacy (MPA) with frailty status. Data represent % inadequacy (<0.5) and % Data Availability adequacy (≥0.5) of micronutrients. Pooled data represent the total No data were used to support the ﬁndings of this study. number of samples (n � 88). P< 0.05 was considered to be signiﬁcant. Conflicts of Interest All authors declare that there are no conﬂicts of interest. physical inactivity in frail subjects. -ough the amount of food is low in the frail group, the quality of diet is almost equal in both groups as evidenced by nutrient density. Authors’ Contributions -e consumption of fruits and vegetables (rich in micronutrients, antioxidants, and ﬁber) was observed to be Conception and design were carried out by GBR and TS. low in frail older adults. A study demonstrated that the Data collection was performed by TS and PSC. Data in- consumption of three portions of fruits and two portions of terpretation and analysis were conducted by GBR, TS, GM, vegetables per day was related to a lower risk of frailty [45]. and BNK. Preparation of the manuscript was contributed by Another study reported an association between antioxidant TS and GBR. Primary responsibility of the ﬁnal content was deﬁciency and reduced muscle strength [10]. A similar taken by GBR. PA and MPA of micronutrients (%) Percentage of MPA Vitamin A Vitamin C iamine Riboﬂavin Niacin Vitamin B6 Folate Vitamin B12 Calcium Zinc Iron Magnesium Phosphorus Selenium MPA 10 Journal of Aging Research action on frailty-advantage JA,” European Journal of Internal Acknowledgments Medicine, vol. 56, pp. 26–32, 2018. [10] B. Bartali, E. A. Frongillo, S. Bandinelli et al., “Low nutrient TS acknowledges the research fellowship from the Indian intake is an essential component of frailty in older persons,” Council of Medical Research, Government of India. -e >e Journals of Gerontology Series A: Biological Sciences and authors are thankful to all the participants in the study. Medical Sciences, vol. 61, no. 6, pp. 589–593, 2006. -e authors sincerely thank Dr. AT Jotheeswaran, World [11] R. B. Biritwum, N. Minicuci, A. E. Yawson et al., “Prevalence Health Organization, Geneva, and Dr. Vivian Isaac, of and factors associated with frailty and disability in older Flinders Rural Health, South Australia, for constructive adults from China, Ghana, India, Mexico, Russia and South criticism and useful discussion in the preparation of the Africa,” Maturitas, vol. 91, pp. 8–18, 2016. manuscript. -e authors also acknowledge the help of Dr. [12] J. J. Llibre Rodriguez, A. M. Prina, D. Acosta et al., “-e S. Sreenivasa Reddy and Dr. M. 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Journal

Journal of Aging Research – Hindawi Publishing Corporation

Published: Jul 10, 2020

References

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B. Bartali, E. A. Frongillo, S. Bandinelli et al.
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R. B. Biritwum, N. Minicuci, A. E. Yawson et al.
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K. Yashoda and N. Aarti
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S. M. Albert, M. Alam, and M. Nizamuddin
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J. R. Wood, B. M. Kaminski, C. Kollman et al.
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C. Kvam, E. Dworsky, A. T. Campbell et al.
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NCEP
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S. S. Jose, M. S. Radhika, N. Balakrishna, G. N. V. Brahmam, and G. Bhanuprakash Reddy
Micronutrient intakes and status assessed by probability approach among the urban adult population of Hyderabad city in South India,

T. Shalini, M. Sivaprasad, N. Balakrishna et al.
Dietary variety increases the probability of nutrient adequacy among adults,

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Nutrient density as a dimension of dietary quality,

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Frailty and Nutritional Status among Urban Older Adults in South India

Frailty and Nutritional Status among Urban Older Adults in South India

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Frailty and Nutritional Status among Urban Older Adults in South India

Frailty and Nutritional Status among Urban Older Adults in South India

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