Dietary patterns and psychosocial health status among elderly in West Bengal-India

ABSTRACT

The health and quality of life, of older persons are commonly affected by physiological and psychological changes and concurrent to the changes that occur in their food choices and consumption patterns due to various biological and psychological reasons. Numerous age-related illnesses and ailments can be prevented, mitigated, or alleviated by proper diet and nutrition. Cross-sectional research was done to examine the food choices, and well-being of the elderly. Using stratified random sampling, 114 homebound senior individuals (>60 y) from high, medium, and low socioeconomic strata (SES) in Kolkata were recruited. Data were gathered by the administration of pre-coded questionnaires, including a semi-quantitative food frequency questionnaire, WHO-SRQ depression’ and WHOQOL-BREIF-26 for measuring Quality of Life, and a Lifestyle questionnaire to assess the general lifestyle of participants (physical activity, social activities, etc.). The data were analysed using descriptive statistics, correlations, the chi-square test, and the non-parametric ANOVA test. The results show that dietary preferences, quality of Life, and lifestyle were significantly associated with gender, socioeconomic position, and marital status. The intake of green leafy vegetables was the same across all three SES groups, however the consumption of fruit was lower among low-SES, women, and widows. These groups also had much greater rates of depression than their peers. Dietary diversity was positively connected to healthy lifestyle, and depression was inversely associated. The study reveals that older adults limit themselves to fewer food groups for biological, environmental and psychological reasons. There is a need dietary education and psychosocial support to improve their health and quality of life.

KEYWORDS:

• Elderly
• dietary diversity
• depression
• quality of life
• perceived risk

Introduction

We now have a longer life expectancy than ever before, approximately 1 in 6 people are over 60 years. The global population of people aged 60 and older will double by 2050 (2.1 billion). Between 2020 and 2050, the number of people aged 80 or older is projected to triple, reaching 426 million (WHO’s work on the UN Decade of Healthy Ageing 2021–2030, n.d.). On a physiological level, aging is the result of an accumulation of numerous types of molecular and cellular damage (Preston & Biddell, 2021). As a result, physical and mental abilities gradually deteriorate, disease risk rises, and eventually death occurs. Ageing is frequently accompanied by other phases of life in addition to biological changes, such as retirement, moving to a more suited home, and losing friends and loved ones. While longevity can have advantages and contribute to society, it is important to prioritise health. Research suggests that the percentage of life spent in excellent health remains unchanged, indicating that the extra years are frequently associated by physical and mental health issues (Marx et al., 2017). If people live longer in good health and within a supportive community, they will have the same opportunities to pursue their passions as someone much younger (Scott et al., 2021).

Dietary profile impacts not only physical but mental health through brain composition, structure, function, hormones, neuropeptides, neurotransmitters, and microbiota-gut-brain axis, affecting stress, inflammation, and cognitive function (Adan et al., 2019). Further, mental health is an integral and indispensable aspect of human health, and an unhealthy lifestyle is associated with poor mental health. The incorporation of micro- and macronutrients in a well-balanced and varied diet, along with a healthy lifestyle, is especially important when considering global human aging and the effects of stress over a lifetime. (Muscaritoli, 2021)

Challenges of aging

As individuals age, they consume less and make different eating choices leading to lower nutritional intakes (Drewnowski & Evans, 2001). A recent analysis of energy intake data from healthy older (70 years) and younger (26 years) adults revealed a difference in energy intake of approximately 16–20% between the groups, equating to a decrease of approximately 0.5% per year (Giezenaar et al., 2016) this compares to previous estimates of a decline in energy intake of approximately 25–30% between young adulthood and older age (Giezenaar et al., 2016; Nieuwenhuizen et al., 2010). Eating behaviour may be impacted by physiological changes brought on by ageing, such as satiation, tooth problems, and sensory deficits. As a result of eating more slowly, consuming smaller meals, and snacking less, older adults may consume less food and ultimately lose weight (Giezenaar et al., 2016; Nieuwenhuizen et al., 2010; Shlisky et al., 2017). Further, the attitudes and beliefs among older persons can also interfere with food choice as they are anchored in individuals’ sense of social and personal identities, such as region, community, socioeconomic class, health status, gender, and marital status (Bisogni et al., 2002; Furst et al., 1996). These changes can impact their quality of life (including physical, mental, social, spiritual, and environmental aspects). Also, factors, such as medication and poor appetite, can impact diet quality of older adults (Bloom et al., 2017), with significant ramifications for nutritional risk and poorer quality of life. In a number of studies of older adults, monotonous, low-quality, and low-diversity diets have been found to be associated with comparable messages regarding diet quality (Bartali et al., 2003; Irz et al., 2014). These changes are likely to affect nutritional risk, as the need for a more nutrient-dense diet may coincide with a time when physical limitations begin to impact food access and availability.

Further elderly population are also vulnerable to mental health issues. One of the most pressing public health concerns is the prevalence of mental illness among the elderly, which is linked to greater rates of disability, early death, and medical costs. Depression is a significant problem among older adults (Pilania et al., 2019; Zenebe et al., 2021). The common symptoms include loss of appetite, sleeping disturbance, difficulties in accepting the problems associated with ageing, mood swings, etc. Studies have found that elderly widows are more depressed than a those with surviving spouse. Most widows generally skip meals, they also lose interest in food preparation, after the death of their spouse (Quandt et al., 2010), and also reduced daily contact and communication with others (Carr et al., 2000; Ross et al., 1993). The impact of widowhood on eating habits and nutritional well-being has gained increasing attention in recent years. Understanding the interplay between widowhood, cultural norms, social support systems, and dietary patterns is crucial for addressing the nutritional needs and overall health of widows.

This study among the elderly from Kolkata, India is based on the conceptual framework of the food choice process model (Furst et al., 1996). This model views the food choice process as having three major components: (1) Life Course (personal roles and the social, cultural, and physical environments to which a person has been previously exposed); (2) Influences (Ideals, Personal Factors, Resources, Social Framework, and Food Context influencing food choice); and (3) Personal System (Value negotiation including Sensory Perceptions, Economic considerations, Health/Nutrition, Convenience, Managing Relationships, and Quality). The conceptual framework of the food choice process model offers several perspectives on the food choosing process. Using this approach, dietary preferences and well-being ratings of the elderly were explored.

Method

Design

A community-based situation analysis study using stratified random sampling was conducted. Stratification was based on socioeconomic status. The study was carried out in the metro city Kolkata, India.

Sample size

For an exploratory study, a minimum sample of 30 in each of the socio-economic category would suffice to make comparisons (a total sample of 90). However, a, sample size of 120 elderly was decided for the situation analysis with 40 participants in each socioeconomic stratum, to account for incomplete or missing data. The final sample included 38 elderly willing participants from each the three socioeconomic groups and the total sample of the study was 114.

Income grouping was also based on the number of the bedrooms in the house (1 or no bedroom as low income group (LIG), 2-bed rooms—Middle income group (MIG) and, 3 or more bed rooms—high income group (HIG). The type of the house and ownership were also considered as indicators for socioeconomic status (Owned or rented). In addition, literacy status, Ownership of a car (Number of cars and type of cars), Occupation, and source of income were considered for the income group stratification. (The classification of different income groups namely Economically Weaker Section (EWS) are people with annual income of <1.5 Lakhs per annum, Low Income Group (LIG) are people with annual income of 1.5-3 Lakhs per annum, Middle Income Group (MIG) are people with annual income 3-10 Lakhs per annum and High Income Group (HIG are people with annual income >10 Lakhs per annum as defined by a Ministry of Housing and Urban Poverty Alleviation (MHUPA) in India (Statistita.com,2021).

Ethical considerations

The Institutional Ethics Committee of the ICMR-National Institute of Nutrition reviewed and approved the study (Protocol Number 09/2013/1) older adults individuals (above 60 years) both men and women, living in the community formed the sample for the study. The study participants were randomly selected from the low-, middle- and high-income groups from urban areas. In order to include all income classes, care was taken to include geographical places such as slum, middle-income residential, and high-income areas. Data was collected over the duration of two months.

Inclusion criteria

Individuals aged above 60 years, willing to participate were included in the study. Those suffering from chronic diseases like hypertension, diabetes, chronic obstructive pulmonary disorders, tuberculosis, individuals who underwent a major surgery like CABG (coronary artery bypass graft) (6 months prior) to the study were included

Exclusion criteria

Individuals above 60 years who had speech defects, memory loss or any other impairment were excluded. Individuals who recently (<6 months) underwent a major surgery, undergoing treatment for major illness like radiation therapy in cancer or dialysis due to chronic kidney failure were also excluded from the study.

Data collection tools

A pre coded close-ended questionnaire was used to assess the socio-economic status and lifestyle (including questions on “Activities during leisure time). Questions relating to physical activity and types of physical activity, and general health were also part of the questionnaire. Pre coded close ended questionnaire was used to collect demographic details of the person, like, name, age, gender, family type, marital status, Occupation, literacy status, etc. Food frequency questionnaire (National Institute of Nutrition, ICMR) was used to assess dietary diversity. This questionnaire includes the various food groups (10 food groups) locally available and also foods traditionally consumed by the participants.

Semi-structured open-ended questionnaire was used to assess dietary intake pattern & health perceptions regarding certain foods. These questions related to the risk perception (health-risk perception and age-risk perception) regarding various foods. For example, what are the foods avoided because of any health risk? ‘What are the foods consumed because it’s good for health?’

To assess the wellbeing of the elderly, World Health Organization Quality of Life Brief Version (here after used as WHOQOL-BREF) was used. Quality of Life is a broad ranging concept affected in a complex way by the person’s physical health, psychological state, level of independence, social relationships, personal beliefs and their relationship to salient features of their environment. The WHOQOL-BREF, an abbreviated 26 item version of the WHOQOL-100 is a validated tool. It assesses quality of life in four domains viz. Physical health (7 items), Psychological health (6 items), Social relationships (3 items), and Environmental health (8 items). It has been used in the Indian context among different age groups including the elderly to assess quality of life (Kumar & Majumdar, 2014; Singh et al., 2022).

The symptoms of depression were assessed using the WHO SRQ-20 scale. The SRQ-20 is a self-report screening tool developed by the World Health Organization specifically for the low and middle income countries and used in the primary healthcare setting. It employs a yes/no answer format and is designed to detect non-specific psychological distress, including suicide ideation (Beusenberg et al., 1994). The tool has been used in the Indian settings earlier (Arora & Kalra, 2023; Brinda et al., 2014; Fahey et al., 2014).

Pre-testing

All the questionnaires were pre-tested among 12 Bengali older adults in Hyderabad. Certain changes were made in the questionnaires based on the pre-test. Initially the questionnaire did not have ‘Type of Car owned and number of cars owned’. During pretesting we found that both High income and Middle-income groups owned cars, the question ‘Do you own a car?’ was therefore not very discriminatory hence a question on type of the vehicle (hatch back, sedan, SUV etc) and number of vehicles owned was included. Another inclusion was a question regarding ‘frequency of medical check-up’ which could shed light on health seeking behaviours and health condition awareness as most of their concerns were about health.

In the food frequency questionnaire, changes were made based on the locally available and traditional foods like puffed rice and rice flakes, in pulses and legumes groups’ soyabean and dry peas were included. In the vegetables and Green leafy vegetables category locally and traditionally accepted vegetables and greens such as yam, Colocasia, figs, lima beans and Malabar spinach were included. It was found that noodles and oats were part of regular diet among some respondents and so it was included in the food frequency questionnaire.

Data Collection

Before administering the questionnaire written informed consent was taken from each participant. Only those who consented were interviewed. The questionnaires were administered in an interview mode. Data were entered into an Excel sheet for the descriptive statistical analysis, using SPSS 19.0 and a probability of < 0.05 chance of error was considered significant.

Results

Demographic profile of the respondents

The Demographic results are presented in Table 1. The age of the participants ranged from 60 to 87 years. The highest number of participants were present in the age group 60–70 years (n = 55), followed by 71–80 years (n = 42) and >80 years (n = 17). A higher number of women 51.8% (n = 59) participated in the study. Among those aged 60–70 years and 71 = 80 years, more women participants were present, however in the >80 years group more men subjects took part than women. The literacy status showed that 40.4% of the participants completed college education while 21% were illiterates. Most participants (70%) lived in nuclear families and 63% lived with their spouse, and the others (42%) were widowed (Table 1).

Table 1. Demographic profile of the respondents.

Attribute	60–70 years (n = 55)	71–80 years (n = 42)	>80 years (n = 17)	Total 114
Gender
Men	25(45.5%)	20(47.6%)	10(58.8.2%)	55(48.2%)
Femen	30(54.5%)	22(52.4%)	7 (41.2%)	59(51.8%)
Literacy status
Illiterate
Read and write	11(20%)	7 (16.7%)	3 (17.6%)	21 (18.4%)
Only Primary education	2(3.6%)	1(2.4%)	1(5.9%)	4(3.5%)
5^th −9^th class	3(5.5%)	6(14.3%)	1(5.9%)	10(8.8%)
10^th or 12^th pass	(9.1%)	9(21.4%)	0(0%)	14 (12.3%)
College and above	7 (12.7%)	5(11.9%)	7(41.2%)	19(16.7%)
Family				46(40.4%)
Joint	27(49.1%)	14(33.3%)	5(29.4%)
Nuclear	13(23.6%)	13 (31.0%)	6(35.3%)	32(28.1%)
Extended nuclear	39(69.1%)	25(35.7%)	7(41.2%)	70(61.4%)
Marital Status				12(10.5%)
With Spouse	4(7.3%)	4(9.5%)	4(23.5%)
Widowed	38(69.1%)	21 (50.5%)	4 (23.5%)	63 (55.3%)
Single	14 (25.5%)	21 (50%)	10 (58.8%)	45 (39.5%)
Divorced	3 (5.5%)	0	3 (17.6%)	6 (5.2%)
Socio Economic Status		0	0	0
Low	14(25.5%)	19(45.2%)	5(29.4%)	38(33.3%)
Medium	20(36.4%)	11(26.2%)	7(41.2%)	38(33.3%)
High	21(38.2%)	12(28.6%)	5(29.4%)	38(33.3%)

Frequency of meal consumption

About 78.1% of respondents reported that they consume three meals per day and a small proportion (5.3%) was consuming only one meal a day. Around 47% reported that they do not snack between main meals. While 50% consumed beverages (tea, coffee), and about 7% consumed them five times a day. Only 4.4% reported that they do not consume any beverages. (Figure 1)

Figure 1. Frequency of meal, snack, and beverage consumption among the geriatric population in Kolkata.

Type and frequency of engaging in physical activity

Among the participants 8.8% practiced yoga regularly, 27.2% went for morning walks, and 27.2% followed other types of physical activity. Overall, 63.2% of the respondents engage in some form of physical activity and among them, 46.5% were exercising every day (Figure 2). Nearly 37% of the subjects never engaged in any physical activity (Table 2)

Figure 2. Frequency of engaging in physical activity.

Table 2. Type and frequency of engaging in physical activity.

Type of exercise	Percentage
Yoga	8.8%
Morning walk	27.2%
Gym exercise	0%
Others	27.2%
No exercise	40.4%

Health problems and health seeking behaviour

Over 51% respondents reported that they were suffering from various types of gastrointestinal disorders, 36.9% respondents said they were hypertensive, 21.6% were diabetic and 28.8% were suffering from joint pains. About 44.7% were going for regular medical check-up, and 39.5% reported that they seek medical help when they feel Sick and 15.8% reported that they do not go for medical check-up. When asked about their dental health, 15.8% reported that they did not have teeth, however, only 7% had dentures. About a fifth (19.3%) were able to chew food only partially, and the rest were able to chew the foods normally (Table 3)

Table 3. Various health problems being experienced by the sample population.

Most common health problems	Percentage
Hypertension	36.9%
Diabetes	21.6%
Joint pain	28.8%
Gastro Intestinal Problem	51.3%
Medical Check up
Regular Check up	44.7%
No Check up	15.8%
When only sick	39.5%
Dental Status
Dental issues Present (reported)	57.9%
Dental issues Absent(reported)	15.8%
Denture	7%

Mental health

Two wellbeing parameters namely, Depression and Quality of Life were considered to assess mental health. On the depression scale, 8 is the median, a score of <8 is considered as ‘no depression’ and a score of >8, is considered as showing symptoms of depression as per the self-reporting questionnaire manual (Beusenberg et al., 1994). The mean depression score was higher among the study participants (8.8 ± 2.1 (Table 5)) and prevalence of depression was more among women (69.5%) than men (43.6%). Participants above 70 years of age had more depression (64.4%). Fewer number of participants from high socio-economic group showed symptoms of depression compared to low socio-economic groups (60.5% Vs. 76.3%) nonetheless both groups had high rates of depression. Further those who were widowed showed higher rates of depression compared to those living with their spouse (Table 4).

Table 4. Prevalence of depression in the sample population.

	<8(Median)(No Depression)	≥8(median)(Depression present)
Gender
Men	56.4%	43.6%
Femen	30.5%	69.5%
Age
60–70	50.9%	49.1%
>70	35.6%	64.4%
SES
Low	23.7%	76.3%
Middle	44.7%	55.3%
High	60.5%	39.5%
Marital status
Without spouse	33.3%	66.7%
Withspouse	50.8%	49.2%

Table 5. Total depression score.

Depression	Mean Std Deviation
Depression	8.32 ± 4.48

Quality of life and age, gender and socio-economic status

WHOQOL-BREF was used to assess the quality of life in the elderly in the physical, psychological, environmental and social relation domains, and it was observed that participants between the age 60 years to 70 years had better quality of life (higher mean) in all the domains compared to those who are >70 years of age. Gender differences were also seen in quality of life with men having better quality of life compared to women. Differences were also observed with respect to socio economic status. The High-income group had higher mean in all the domains (Table 6)

Table 6. Mean difference of quality of life with SES, gender & Age.

	Physical	Psychological	Environmental	Social Relations
Age
60–70	63.22 ± 17.56	62.17 ± 18.38	62.73 ± 15.32	36.49 ± 13.98
>70	51.31 ± 20.70	55.75 ± 23.42	59.66 ± 17.92	32.31 ± 13.53
Gender
Men	65.42 ± 18.87	67.27 ± 19.74	66.89 ± 14.70	37.73 ± 12.98
Femen	49.25 ± 18.04	50.79 ± 19.73	55.78 ± 16.80	31.15 ± 13.98
SES
Low	46.66 ± 17.63	46.24 ± 19.72	49.55 ± 15.97	29.42 ± 14.45
Middle	59.00 ± 18.51	60.89 ± 20.34	63.61 ± 12.80	36.39 ± 13.65
High	65.50 ± 19.74	68.97 ± 17.75	70.26 ± 14.30	37.16 ± 12.37

Dietary diversity

The dietary diversity was assessed to see the variety of food group intake over a year amongst the study participants. 64.6% of study participants consumed a variety of vegetables and around 54.7% consumed green leafy vegetables. However, milk and milk products were consumed by only 39.82% and fruits by only 36.9% on a daily basis. Millet consumption was almost nil and consumption of nuts was also reported to be low at 18.7%. Animal foods were consumed by 43.42% of study population (Table 7).

Table 7. Mean percentage of dietary diversity in a year in geriatrics population in Kolkata.

Food groups	Actual mean and SD	Mean (%) + SD
Cereals	2.18 ± 0.645	54.60 ± 16.14
Millets	0	0
Pulses	3.77 ± 1.89	47.14 ± 23.63
Animal foods	1.99 ± 1.18	39.82 ± 14.89
Milk and milk products	1.76 ± 1.30	43.42 ± 34.98
Nuts	0.5614 ± 0.98	18.71 ± 32.89
Vegetables	18.75 ± 4.31	64.66 ± 25.98
Green leafy vegetables	3.83 ± 2.44	54.76 ± 12.56
Fruits	6.64 ± 4.67	36.94 ± 25.98
Oils	1.83 ± 0.62	36.60 ± 12.56
Fats	0.5520 ± 0.79	18.421 26.64

Correlation of diet diversity with depression

The consumption of various food groups amongst participants was correlated with variables of lifestyle and depression. It was observed that consumption of cereals, pulses, nuts, animal foods milk and milk products, vegetables, and fruits showed a significant correlation with lifestyle whereas consumption of green leafy vegetables, oils, and fats had no correlation with lifestyle. Oils and fats also did not show any correlation with depression, but all other (considered) food groups had a correlation with depression (Table 8)

Table 8. Correlation diet diversity with lifestyle and depression.

Food groups	Lifestyle	Depression
Cereals	0.257(**)	−0.212(*)
Pulses	0.422(**)	−0.195(*)
Nuts	0.334(**)	−0.221(*)
Animal foods	0.205(*)	−0.247(**)
Milk and milk products	0.322(**)	−0.276(**)
Vegetables	0.320(**)	−0.314(**)
Green leafy vegetables	0.168	−0.247(**)
Fruits	0.368(**)	−0.237(*)
Oil	0.131	−0.165
Fats	0.150	−0.156

Diet diversity and socio-demographics

The association dietary diversity (variety of food groups) and various socio-demographic variables was examined. There was no significant difference in consumption of cereals in high- and middle-income groups, but comparatively better consumption in variety was seen in lower socioeconomic status group.

Association between diet diversity and gender showed that the men participants had more diversity of foods in their diets than the women. Significant differences in consumption of nuts, animal foods, milk and milk products, vegetables and fruits were seen, with men participants consuming more of these food groups (Table 9).

Table 9. Mean (%) and association of diet diversity with SES, gender, marital status.

Group	Socio Economic Status			Gender			Marital status
	Low	Middle	High	Men	Women	p-value	Widowed/Single	With spouse	p-value
Cereals	1.89 ± 0.31	2.23 ± 0.67	2.42 ± 0.75	2.34 ± 0.77	2.03 ± 0.45	0.011	2.02 ± 0.45	2.28 ± 0.74	0.025
Pulses	3.0 ± 2.0	4.34 ± 1.72	3.97 ± 1.71	4.09 ± 1.70	3.47 ± 2.02	0.082	3.42 ± 1.86	3.95 ± 1.92	0.155
Nuts	0.23 ± 0.58	0.60 ± 1.02	0.84 ± 1.17	0.81 ± 1.14	0.32 ± 0.75	0.008	0.22 ± 0.55	0.74 ± 1.10	0.004
Animal foods	1.52 ± 0.97	2.26 ± 1.28	2.15 ± 1.74	2.30 ± 1.13	1.68 ± 1.16	0.005	1.72 ± 1.16	2.11 ± 1.17	0.098
Milks & Milk Prods.	1.10 ± 1.26	2.0 ± 1.27	2.1 ± 1.15	2.01 ± 1.23	1.47 ± 1.31	0.025	1.48 ± 1.44	1.85 ± 1.20	0.152
Vegetable	16.10 + 5.04	19.52 + 3.12	20.55 + 3.31	19.94 ± 3.37	17.62 ± 4.81	0.004	17.22 ± 4.48	19.62 ± 4.04	0.004
GLVs	3.23 ± 2.29	3.78 ± 2.39	4.47 ± 2.55	4.07 ± 2.43	3.61 ± 2.46	0.316	3.46 ± 2.52	3.98 ± 2.42	0.285
Fruits	3.23 ± 2.29	3.78 ± 2.39	4.47 ± 2.55	7.54 ± 4.60	5.81 ± 4.62	0.048	5.02 ± 3.98	7.46 ± 4.77	0.006
Oil	1.57 ± 0.64	1.89+.05	2.02 ± 0.62	1.92 ± 0.66	1.74 ± 0.57	0.128	1.71 ± 0.66	1.90 ± 0.62	0.133
Fat	0.21 ± 0.62	0.76 ± 0.71	0.68 ± 0.93	0.67 ± 0.86	0.44 ± 0.72	0.122	0.46 ± 0.81	0.58 ± 0.75	0.437

When diet diversity and marital status were assessed, animal foods, vegetables and fruit as well as nuts’ consumption were found to be lesser among those who were single/widowed than those living with their spouses.

Changes in food consumption due to risk perception

It was observed that there were certain patterns in consumption of certain foods because of perceived health risk and certain taboos. Around 48.2% of the participants attributed some risk to certain foods (Table 10).

Table 10. Alterations in food consumption due to risk perception.

Reasons	Percentage
Self-reasoned Risk(realization, interest)	55 (48.2%)
Doctor Advised	38 (33.3%)
Dietician advised	21 (18.4%)
Family and care giver	15 (13.1%)

Perceived risks from various food groups

The health risk attributed included acidity, gas, indigestion about 40% of the participants avoided cereals and about 20% avoided citrus fruits for these reasons. Participants reported they avoided green banana due to fear of constipation (18%), while 32.4% did not consume nuts, milk, egg, chicken as they perceive that these would leads to obesity, overweight and hypertension. Over 21% people reported that they avoided lentils and legumes, tomato due to risk of gout (Table 11).

Table 11. Perceived risks from various food groups.

Food consumed less or not consumed	% of population	Health related Perceived risk
Cereals
Bread, Semolina, Wheat, Rice	46(40%)	Gas
Pulses		Acidity
Bengal gram, black gram,	20(17.5%)	Colitis
Animal foods-		Indigestion
Eggs	13(11.4%)	Diarrhoea
Milk and curds		Mucous secretion
Green leafy Vegetables	35 (30.7%)
Vegetables and Fruits	25 (21.9%)
Cauliflower	10 (8.7%)
Apple, Guava, Grapes, Jackfruit, Litchi	20 (17.5%)
Citrus fruits	20(17.5%)
Oily and fried foods,butter and ghee	21(18.4%)
Green banana	21(18.4%)	Constipation
Chicken, egg	10(8.7%)
Rice flakes	6(5.2%)
Guava and cucumber	40 (35.08%)	Chewing problem
All nuts	42 (36.8%)
Fruits		Diabetes
Mango, Banana, grapes, pineapple, Sapota	25(21.9%)
Roots and tubers
Potato, carrot, Beet	17(14.9%)
Nuts, eggs, milk and milk products(curd, Paneer) mutton, chicken,	37(32.4%)	Overweight, Hypercholesterolemia Hypertension CHD
Lentil, ladies finger, tomato, beans, drumstick seeds,	25(21.9%)	Gout
Colocassia,Brinjal, Egg	15(13.1%)	Allergy
Milk products, papaya, radish, chicken	10(8.7%)	Strong smell
	Age related perceived risk
Animal foods-egg, mutton,liver Ghee, butter, junk foods (caffeinated drinks) Rice and Roti	65(57%) 70(61.4%) 26(22.8%)	limited consumption

Table 12 shows the foods that were reported to have been not been consumed or avoided by the respondents due to social, family and religious belief. Over 21% people avoided lentils because they considered these as ‘non-vegetarian’ food, snake gourd was avoided because it looks like a ‘cow’s horn’. About 26.3% and 22.8% people have stopped consumption of certain foods due to personal dislike or due to family preference. A few of them (9.6%) reported that they were avoiding some of the foods due to ‘special reason’ (like departed spouse’s favourite food, foods sacrificed during religious occasions).

Table 12. Food intake altered due to social/family/religious belief.

Foods	Percentage	Perceived risk for other issues
Variety of fruits and vegetables pulses, milk and milk products	25(21.9%)	Taboos
	30(26.3%)	Personal dislike
	26(22.8%)	Family preference
	11(9.6%)	Other reasons (husband’s death, some fruits avoided because they were given at mother’s funeral)
	20(17.5%)	loneliness
	45(39.4%)	Expensive

Discussion

The present study on the food choices, dietary patterns and wellbeing among elderly was carried out in Kolkata, a metro city of Eastern India among 114 elderly individuals using the food choice process model. The study focused on dietary intakes (in terms of diet diversity) and psychological well-being of homebound older adults in Kolkata. Study evaluated older adults’ food choices and the perception of food risk based on their age, and related factors. Further, the association between socioeconomic status (SES), gender, age, and marital status, diet diversity, lifestyle, quality of life, and depression were also assessed. Social, cultural, and psychological factors were found affecting the food choices of the elderly and restricting diversity. Better social and psychological environment improves self-efficacy, psychological status. As seen in this study personal factors especially maintaining relationship and certain customs lead to reduced diversity. An improvement of these factors leads to an amelioration of dietary intake both in terms of quality and quantity (Poggiogalle et al., 2021). The consumption of green leafy vegetables and other vegetables was high among older adults of Kolkata as reported in an earlier study (Arlappa et al., 2010) for the population of West Bengal. There is general acceptability and availability of greens in the region.

Psychological wellbeing assessed by WHOQOL and WHOSRQ tests showed that depression was associated with socio-economic status, gender and marital status. Elders in lower socio economic status, women, and widows were more vulnerable to depression. A study that assessed Quality of Life (QOL) among 300 elderly subjects, focusing on activities of daily living (ADLs) and socio-demographic factors showed that QOL score was average among the elderly population, but low in the social relationship domain. The authors suggested health education and increased social relationships to improve QOL among the elderly population (Kumar & Majumdar, 2014). Quality Of Life is an indicator of wellbeing in elderly. Inadequate finance, inadequate social relationship (Bowling, 2005; Farquhar, 1995), loneliness, insomnia, poor physical health were found to be associated with poor quality of life (Guire & Boyod, 2004; Lasisi & Gureje, 2011). SES, family structure, and physical health were found to be significantly associated with quality of life in the present study. In all four domains used to evaluate QoL, women scored lower than men. Those over the age of 70 and widows had a poorer quality of life and those with a middle or high income had a better quality of life than those with a low income (Sasson & Umberson, 2014). A prospective cohort study among elderly in the United States showed men and women do not differ in trajectories of depressive symptoms following widowhood, the study however adds that women are distinctly disadvantaged as they are more likely to become widowed and under are in more un favourable conditions. The situation may further be exacerbated in low- and middle-income settings where economic and social stress are higher. As in the present study women reported more depressive symptoms than men, and widows tended to exhibit more symptoms than women living with spouse. Similar results were reported in a study among western population (Djernes, 2006).

Lifestyle (physical activity, smoking, consumption of alcohol and other habits) practices were poorer among lower SES group, women, and widows. However, some studies reported middle- and high-income groups in India, had sedentary lifestyle and lower physical activity than lower income group (Dey et al., 2012; Steptoe & Zaninotto, 2020) Widowhood and living alone are associated with a lack of resources and motivation to participate in meaningful physical and social activities, thereby contributing to poor well-being and negative psychological symptoms in this population. Long periods of widowhood, a declining income, and the management of multiple chronic ailments have been found to be associated with these negative psychological symptoms in elderly widows (Digiacomo et al., 2013; Sasson & Umberson, 2014).

Dietary variety and socioeconomic status were found to have a significant correlation. Seniors who have low-income have greater incidence of food insecurity. Similar results were found in study Pirrie et al. (2020). The consumption of milk and milk products, animal source foods, fruits and vegetables were significantly lower in the low SES group than in the middle and high SES groups. Diets of affluent senior citizens are enriched with lean meat, fish, milk, vegetables, and fibre, whereas the diets of low-income subjects are replete with with refined grains and added fat, which are low in micronutrients (Sharma et al., 2020). Poor nutrition knowledge, low budgetary resources, and social and environmental factors may be the leading cause of poor diet quality in this group (Fekete & Weyers, 2016). Gender and marital status were significantly associated with dietary diversity. According to studies, older men’s eating habits are more strongly correlated with their living situation and level of income, with wives having healthier routines (Vajdi & Farhangi, 2020). Men with a spouse had healthier dietary habits, while those without a spouse and low income were at higher risk. For women, income was more consistently associated with dietary indicators than living situation. However, income had a less consistent effect on the dietary patterns of older women than older men. Low socioeconomic status and living alone were associated with lower fruit and vegetable consumption. Widowed elderly women and those with a low socioeconomic status had a limited variety of foods in their diets (Vajdi & Farhangi, 2020) as was also found in the present study. There was a strong correlation between the consumption of nuts, milk and milk products, animal foods, and fruits and the marital status of the individual.

Snacking habits among the participants varied, 43% did not snack while the remaining snacked either once or twice. Snacking 2 to 3 times in between main meals increased the variety in the diet (Almoraie et al., 2021). However, in the current study only 14% snacked 2 to 3 times a day (Figure 1)

Dietary diversity, lifestyle, and depression were associated present study. Milk and milk products, vegetables, Green leafy vegetables, and fruits showed a modest association, indicating the importance of these food groups for enhancing wellbeing. Dietary diversity is also significantly correlated with lifestyle. Those who do not smoke, do not consume alcohol, and engage in regular exercise were observed to consume nuts, a variety of cereals, animal foods (particularly milk and milk products), vegetables, and a variety of fruits. The current study showed a negative association between depression and dietary diversity. Reduced consumption of animal foods, milk and milk products, green leafy vegetables and other vegetables, and fruits may contribute to a higher depression rate. According to a study by Sinclair et al. (2007), omega-3 fatty acids may help to alleviate depression. Age-related depression may be mitigated by regular fish consumption. Omega-3 fatty acids are present in fatty cold-water fish such as salmon and mackerel, as well as in vegetable seeds and oils such as flaxseed, walnuts, almonds, etc. In addition, folate and vitamin B12 reduce depression symptoms, with folate naturally occurring in green leafy vegetables, orange juice, berries, starchy vegetables, eggs, beans, and whole grains. As the study participants consumed lower vegetables and fruits it is more likely to cause nutrient deficiencies and thereby decrease their wellbeing. According to another study, depressed individuals had lower folate levels than non-depressed psychiatric patients (Bender et al., 2017). Also, a Taiwanese study (Tsai et al., 2012) found that vegetables appear to protect against depressive symptoms.

In their study on Dietary diversity and healthy life expectancy authors Miyamoto et al. (2019), after adjusting for socioeconomic characteristics found that populations with higher nutritional diversity live longer and healthier lives. In the present study, perceived health and age-related risk perception altered the food preferences of older adults. They avoided certain foods or food groups out of concern for various diseases. Forty percent of individuals avoided bread, semolina, wheat, and rice because they feared it would cause ‘gas and acidity’, while 18.4% believed that green bananas cause constipation. However, they are not sure of it and said it’s something they heard when they were young. Neighbours also tend to influence their perception, and in some cases after trying certain foods for relatively many times they discover that they are allergic to that food or that it does not agree with them. Some fruits and salads are avoided by 42% of subjects due to chewing difficulties; some of these individuals stated that they ‘did not want to lose their remaining teeth’ Nearly 22% of the elderly avoided lentils, ladies’ finger, tomatoes, beans, and drumstick seeds due to gout concerns. They believed that these foods may exacerbate joint pain. Beans and fruits raise uric acid levels. Approximately 32% of respondents believed that nuts, eggs, milk and milk products, chicken, and lamb should not be consumed because they are high in fat and cause hypercholesterolemia, hypertension, and coronary artery disease. Some respondents stated that these foods ‘contain high levels of protein that should not be consumed by elderly individuals’ and others reported all roots and tubers as well as fruits such as mango, banana, grapes, pineapple, and sapodilla raise the blood sugar level. About 36.8% feared an increase in blood sugar levels and hence avoided fruits; A few (8.7%) individuals avoided milk products, papaya, radishes, and chicken because they had a purgative effect. About 13.1% of individuals avoided brinjal, colocasia, and eggs due as they cause allergy. They developed an allergic reaction as children and have avoided these foods out of fear that the symptoms will return. In a previous study by Christie et al. (2002), it was discovered that people avoided tree nuts and legumes out of concern for food allergies. After the allergy test, one-third of the subjects were determined to be allergic to a specific food, while the remaining subjects were normal but avoided the food out of fear of an allergic reaction.

Age-related risk perception limited consumption of animal source foods such as eggs, lamb, ghee butter, processed food, and caffeinated drinks, among others. Approximately 61% of respondents believed that the quantity of food consumed should be restricted due to ageing. Rice and roti should be consumed in moderation at their age. Around 18% of the respondents were advised by their doctor to watch their diet due to their age. While some elderly individuals (33%) were given dietary restrictions due to their health conditions others practise this restriction voluntarily. Food taboos was an additional intriguing perspective on food choice. Indian society cultural norms and traditions, including dietary restrictions, can lead to imbalances and deficiencies in their diets. Indian widows face nutritional challenges, affecting their health and well-being, including malnutrition, immune function, chronic diseases, and mental health issues like depression and anxiety. About 22% of the subjects said ‘lentil was a non-vegetarian dal and being a widow and vegetarian, we are not supposed to eat lentils’ some of them said ‘though we know it is high in protein we cannot eat’ some people said ‘snake gourd looks like cow’s horn and so we don’t eat it’ etc. One Subject said ‘buying milk is not a problem for me but I don’t feel like drinking milk’. Family preference also influenced food choice. Some (22.8%), respondents stated that they loved to eat all kind of foods but it is not possible to eat their favourite food item being in a joint family. An elderly lady said ‘Paneer (cottage cheese) is my favourite item but I’m staying with my daughter who doesn’t like it so she won’t cook’. Another said ‘Figs are very nutritious; I know it contains iron but my wife doesn’t cook it at all because family members do not eat it’. Some women stop eating fruits and their favourite foods after the death of their husbands. One elderly lady said ‘my husband loved to eat all kinds of dal, after his death I could not eat’. Some people distributed their favourite fruits at their mothers’ funereal, therefore, they cannot eat that food throughout their life. Loneliness was also reported as the reason for non-consumption, single dwellers don’t feel like eating fruits, some people said ‘it’s a kind of lethargy’, or they lost interest in cooking and food preparation because of restricted mobility. Similar findings were reported (McKie et al., 2000) where problems with mobility and in carrying food home from the shop might cause a reduction in older people´s own cooking. As a result, they purchased and consumed more semi-prepared and prepared foods. Women with difficulty preparing meals consumed more snacks (Gustafsson & Sidenvall, 2002). Financial condition is also related to health risk perception. They stated that in order to satisfy their hunger, they consumed only energy-dense foods such as rice and potatoes. Previous research has shown that nutritional benefits and dietary quality are dependent on socioeconomic status, perceived food price barriers, and perceived dietary quality benefits (DQI).

Conclusion

In conclusion, this research provides insight into the intricate relationship between food preferences, eating habits, and overall health among elderly individuals in Kolkata, India. It demonstrates that a range of social, cultural, and psychological elements have an effect on food preferences and the variety of foods consumed, which in turn affects overall health and wellness. Dietary habits and psychological wellness are greatly influenced by socioeconomic level, gender, marital status, and lifestyle. Individuals with low socioeconomic level, being widowed, and living alone have been shown to have less dietary variety and less healthy lifestyle habits, which may contribute to a higher likelihood of experiencing depression and other adverse psychological symptoms. Moreover, eating choices are influenced by cultural food taboos and age-related risk perception, which may sometimes result in nutritional shortages and imbalanced diets. To enhance the food intake and general wellbeing of older adults in comparable situations, it is important to address these complex aspects by implementing treatments that focus on social support, nutritional education, and health promotion.

Disclosure statement

No potential conflict of interest was reported by the author(s).