Mediterranean diet adherence,social capital and health related quality of life in the older adults of Crete,Greece: The MINOA study

Abstract

BACKGROUND:

Adherence to the Mediterranean Diet (MD), a sustainable dietary pattern with multiple benefits to health, environment, economy and society is decreasing even in the older adults in rural Crete; the prototype pattern from the 7 Country Study.

OBJECTIVE:

Investigate social and health related factors that may be perceived as barriers to adherence to the MD, among older adults, living in rural region of Crete, Greece.

METHODS:

Evaluate a) adherence to the Mediterranean dietary pattern using the MedDietScore b) dietary intake using the Water Balance Questionnaire (WBQ) c) social connections using the Social Capital Questionnaire including the Physical and Mental Component of Health (PCS and MCS, respectively) and d) health-related quality of life (HRQL) using the SF-36 Questionnaire, among older adults residing in the Municipality of Minoa; a Cretan rural area. A total of 436 older adults (>65 years, 58% men) were enrolled.

RESULTS:

Mean MedDietScore was moderate (31.9±3.6) and was found higher in males (32.9±3.4 vs 30.6±3.4; p < 0.001). Total social capital was 75 (68,80) with no significant differences between genders. The PCS was 45 (37,52) and the MCS 47 (40,54), males achieving a higher score (p < 0.0001 and p < 0.01 respectively). Results of linear regression, for adherence of the MD, showed sex (p < 0.0001), marital status (p = 0.039), “growing vegetables-fruits” (p = 0.014) and car ownership (p = 0.044), associated with MedDietScore.

CONCLUSIONS:

Older adults living in Crete, adhere moderately to the MD, with potential barriers being lower PCS and MCS and weak support provided by family and community structures as quantified by low scores in social capital and health-related quality of life.

Keywords

Mediterranean diet MedDietScore social capital SF-36 older adults Crete

1 Introduction

The Mediterranean Diet (MD) is widely recognized as a dietary pattern associated with significant improvements in health status, low environmental impact, local economic gains and strong links with social and cultural assets in the Mediterranean [1]. Despite these well-documented benefits, recent studies show that adherence to the MD pattern is decreasing in the Mediterranean areas. Recent studies in Crete have shown that the population now follows more of a westernised diet [3 –5].

Cretans in rural areas participated in the Seven Countries Study in the late 1950 s; this study was first to propose the link between diet and health and described the main characteristics of the MD [6]. It is, therefore, of particular importance not only to evaluate current dietary habits of the older adults in rural areas in Crete but also to further understand barriers that potentially prohibit adherence to the MD. Barriers include the ability to access, prepare and consume foods that characterise the MD are complex, particularly in older age; among others social and health related factors must be investigated.

Social related factors captured into the concept of Social Capital (SC) allow us to evaluate the interaction of the individual with community or family structures of support and, in this context, interpret habits and health conditions [7]. Social Capital reflects participation in community affairs, social networks and information channels, the sharing of values and support among people [8 –12] and its components are associated with various health behaviors [13 –16] and might influence indicators of health including mortality [12 , 18]. It may be hypothesised that particularly in older age, SC may be associated with dietary choices and/or the adherence to MD as it may influence accessing, preparing and consuming foods that characterised the MD; there is no evidence to support this hypothesis.

Health related factors may be complex and include a variety of indicators. Among those, self-rated health (Health Related Quality of Life HRQL [19] allows the evaluation of individual perception on health status and general wellbeing, although without reference to any specific medical condition. Studies show that self-rated health is a good predictor of morbidity and mortality, linked to objective health conditions particularly in older adults [20, 21]. Perception of health and well-being may therefore interfere with accessing, preparing and consuming foods that characterised the MD, thus with adherence to MD. This hypothesis is supported from a cross-sectional study conducted in a Spanish population, which showed that adherence to MD was associated with higher scoring for self-perceived health [22].

Aiming to further investigate low adherence to the MD among the older adults in rural areas in Crete, we launched the study named “Mediterranean diet IN Older Adults” from now on referred to as the MINOA study, also as per the area or research, which was a rural area in Crete. Our objectives were a) to evaluate adherence to the MD using the MedDietScore [23] and b) to investigate social and health related factors that may be perceived as barriers to adherence to the MD using the SC and the HRQL scores in older adults of rural region of Crete. In the present work, we present the design and methodology of the study, with primary reports of various baseline characteristics, social capital, mental and physical health of the participants.

2 Methods

The study protocol was reviewed and approved by the Ethical Committee of the Agricultural University of Athens (181-14/02/2014) and procedures were carried out in accordance to the declaration of Helsinki. All subjects signed a voluntary consent form upon agreeing to participate.

2.1 Participants

The current study is cross-sectional conducted in the rural area of the Municipality of Minoa, Crete, Greece, one of the regions in the 7 Countries Study. According to the latest census, in 2011, 17.563 inhabitants were in the area, of which 5.956 (34%) were over 65 years of age. The study recruited participants from Open Protection Centres for the Elderly. These are public structures where social workers and health professional and other personnel provide to older adults social assistance, first-degree medical care, and recreational activities. In particular, study specifics were provided to two Open Protection Centres for Elderly (KAPI) at the villages Kastelli and Arkalochori of the Municipality of Minoa and all adults enrolled in these centres were invited to participate. Participants enrolled in KAPI that were able to understand and respond to the questionnaire independently were included in the study.

In total 436 volunteers (57.6% males) out of 484 adults over 65 years old were recruited between April 2014 and November 2015 (90% participation rate). Information on sociodemographic and behavioural characteristics, dietary and lifestyle habits, and questionnaires estimating adherence to the Mediterranean Diet, Total Social Capital and Health–Related Quality of Life (HRQL) were gathered via interview, using previously validated questionnaires [34, 35]. Trained health professionals conducted these interviews at the Open Protection Centres for Elderly.

2.2 Socio-demographic data, lifestyle and anthropometric data

Specific questions on sociodemographic characteristics included: age (in years), sex (male/female), and marital status (married /unmarried, divorced or widower). Participants’ educational level was recorded as years of schooling. Education was then categorized into four categories as previously [24]. Financial status was self-reported with the question referring to the mean annual income (in euros) over the past three years. The financial status was then classified into 3 categories [25]. Participants were also asked to report whether they have been previously diagnosed at some point in the past with a specific disease –(Yes or No) from a list of more frequent chronic diseases and conditions, as per the questionnaire (respiratory disease, cardiovascular diseases, arthritis-osteoporosis, diabetes mellitus, hypertensive, dyslipidemias, thyroid diseases, digestive diseases). The total number of diseases were then added for the analysis.

Information on housing tenure, car ownership and growing vegetables & fruits was also recorded using closed ended questions.

Information on smoking status, physical activity and anthropometrics were also collected. At first, smoking status was categorized as (i) currently smoking at least one cigarette per day, (ii) occasional smokers, defined as less than 7 cigarettes per week, (iii) non-smokers, defined as those who had never tried a cigarette, and (iv) former smokers who had stopped smoking for at least one year. A limited number (1%, N = 5) of the sample reported being occasional smokers, and therefore smoking status was categorized as a binary variable: smokers and non-smokers. Data on weight and height were self-reported. Body Mass Index (BMI) was then categorized into three groups: normal, overweight and obese as per guidelines [26].

Physical activity was estimated using the short version of the International Physical Activity Questionnaire (IPAQ) [27]. The minutes per day of vigorous, moderate, and mild-light activity were calculated based on total frequency and intensity of reported activities and/or sitting time per week according to guidelines. The IPAQ questionnaire has been used in other Greek studies, in older adults [3 , 29]. Participants were finally categorized as having intense, moderate, mild physical activity state. Those achieving a score lower than mild were classified as being sedentary.

2.3 Dietary habits and adherence to the Mediterranean diet

2.3.1 Food consumption data

The tool used in the current study for the data collection regarding the food intake was based on the previously validated Water Balance Questionnaire (WBQ) [30]. This is a semi-quantitative food frequency questionnaire (FFQ) that encompasses a total of fifty-eight foods food items, eighteen beverages and water that are most commonly consumed among the specific population. Further details of the WBQ entailing the semi-quantitative FFQ have been already published [30].

Regarding the analysis of the, FFQ firstly, all measurements of the frequency of food consumption were converted into daily measurements. Secondly, the foods were grouped into 10 food groups, according to categorization process reported by Passmore and Eastwood [31], a method used in other nutritional epidemiological studies, also in Greece [32]. The food groups were ten: cereals, potatoes, vegetables, fruits/ fresh juices, meat and meat products, fish and seafood, milk and dairy products pulses-nuts and seeds, added lipids, sugars and syrups. Alcohol, the “11th food group”, was also evaluated. Energy density and alcohol intake recorded from the semi-quantitative FFQ, were calculated by using the USDA National Nutrient Database (USDA, 2010).

2.3.2 Adherence to Mediterranean diet

For estimating the adherence to MD, the MedDietScore questionnaire was used [23]. This score includes 11 main components with a score of 0 to 5 assigned according to servings per week recommended by the Mediterranean dietary pattern. In particular, consumption of dietary components close to the Mediterranean pattern received a positive and higher score (0-5), while consumption of dietary components away from the pattern (red meat and products, poultry, full fat dairy products, and high alcohol intake) received a lower score the higher the consumption (5-0). The score ranges from 0–55 with highest adherence was defined according to highest tertile of diet score or 36–55 as referred by Panagiotakos and colleagues.

2.4 Social capital questionnaire

Social Capital was used to characterize the social relationships and interactions between individuals and groups [17]. Individual social capital of older adults was assessed by the Social Capital Questionnaire (SCQ), developed in Australia [33]. The SCQ, is a practical tool used to measure individual-level social capital, has been translated and validated for the Greek population [34]. The SCQ includes thirty six questions; each question has 4-point scale. Higher scores in each question indicate more social capital.

The SCQ comprises a general Total Social Capital factor as well as six factors in thirty-six questions: Participation in the Local Community, Feelings of Safety, Family/Friends Connections, Value of Life and Social Agency, Tolerance of Diversity and Work Connections [34]. In the present study, the five questions related to work were excluded, since all included individuals were retired. Thus, a total of thirty-one social capital questions were finally included in the specific questionnaire.

2.5 Health-related quality of life. The SF-36 questionnaire

Health-Related Quality Of Life (HRQL) was assessed by using the validated Greek version of the self-administered SF-36 [35, 36]. This tool was translated in more than 50 languages, as part of the International Quality of Life Assessment (IQOLA) Project. The SF-36 is a valid instrument to use in surveys of older adults living in the community [37]. This questionnaire contains 36 items, measuring eight multi-item dimensions of health: physical functioning (PF), role limitations due to physical health problems (RP, role-physical), bodily pain (BP), general health perceptions (GH), vitality (VT), social functioning (SF), role limitations due to emotional problems (RE, role emotional) and mental health (MH). Two different standardized summary Scores of the health-related quality of life can also be calculated from the SF-36: the Physical Component Summary (PCS) on physical health and the Mental Component Summary (MCS) on mental health [38]. All scales contribute in different proportions to the scoring of both PCS and MCS measures [39]. The correct calculation of SF-36 summary measures PCS and MCS required the use of special algorithms provided by license [40].

2.6 Statistical analysis

Descriptive statistics were calculated for all continuous and categorical variables. Continuous variables were checked for normality using Kolmogorov Smirnov normality test and were also graphically assessed using k-desnity and histograms. Normally distributed continuous variables are expressed as mean±standard deviation (SD), and medians –range (25th –75th percentiles) are given for skewed variables. Sex differences for categorical variables (sociodemographic characteristics, daily intake of indicated food groups, Mediterranean Diet (MedDietScore, Social Capital, PCS and HCS) were assessed with Chi-square test, while Student t-test for normally distributed variables and Mann-Whitney U-test for the skewed variables. Multiple linear regression models were used to estimate various participants’ characteristics as predictors of Mediterranean Diet Score. Estimated associations are described in terms of β coefficients and Standard Error (SE) confidence intervals (linear regression models). Significance level was set at 5%. All statistical analyses performed using PASW Statistics 18 (SPSS Inc, Chicago, IL, USA).

3 Results

All participants collaborated with the researchers of the study; participation rate was 90% with no dropouts. The mean age was 75.0±6.2 years, with no significant sex differences Total sample (N = 436; 58% males) mean BMI was 28.0±4.4 kg/m². More females (40.5%) than males (19.1%) were classified as obese (p < 0.001). The sociodemographic characteristics of the participants in the study are presented in Table 1 in total and by sex. In more detail, the majority of the subjects reported primary education (70%), while only 7.3% were illiterate. The level of education was lower in females than males (p < 0.001). The majority of participants were married (75.7%). The annual family income was less than 10.000 euros for the 73.6% of the total sample and had with no differences between genders (p = 0.60). Considering smoking, 14% of all subjects reported current smoking. The majority of females (90.8%) had never smoked. Most of the participants, 57.8%, recorded≥3 diseases, with significant sex differences, 73% of the females and 46.6% of the males (p < 0.0001; data not shown). Most of the total population met the high physical activity level status (44.5%), with significant however, sex differences between IPAQ level; 46% females had moderate levels of physical activity level and 57.4% males had high levels. The majority of the participants (65.8%) reported that they grow vegetables and fruits. Almost the entire sample lived in their own homes (98.6%) and (45.6%) had their own car.

Table 1
Sociodemographic characteristics of older adults, aged > 65 years in Crete, Greece (n = 436)

Total n = 436 Males n = 251 Females n = 185 p-value*

n % n % n %

Age (yrs) 65–≤75 229 52.5 123 49.0 106 57.3 0.09

>75 207 47.5 128 51.0 79 42.7

mean±sd 75±6.2 75.4±6.1 74.4±6.2 0.11

Education (yrs) 0 32 7.3 10 4.0 22 11.9 <0.001

1–6 305 70.0 171 68.1 134 72.4

7–12 76 17.4 55 21.9 21 11.4

>12 23 5.3 15 6.0 8 4.3

mean±sd 6.1±3.5 6.7±3.4 5.4±3.6 <0.001

Marital status married 330 75.7 214 85.3 116 62.7 <0.001

unmarried/widower 106 24.3 37 14.7 69 37.3

Annual family income (euros) <10000 321 73.6 181 72.1 140 75.7 0.60

10000–20000 95 21.8 59 23.5 36 19.5

>20000 20 4.6 11 4.4 9 4.9

Body Mass Index (Kg/m²) <24.9 105 24.1 61 24.3 44 23.8 <0.001

25.0–29.9 208 47.7 142 56.6 66 35.7

≥30.0 123 28.2 48 19.1 75 40.5

mean±sd 28.0±4.4 27.3±3.6 28.9±5.0 <0.001

Smoking never 240 55.2 73 29.1 167 90.8 <0.001

former 134 30.8 126 50.2 8 4.3

current 61 14.0 52 20.7 9 4.9

Physical activity status^a low 105 24.1 55 21.9 50 27.0 <0.001

moderate 137 31.4 52 20.7 85 46.0

high 194 44.5 144 57.4 50 27.0

Growing vegetables and fruits yes 287 65.8 181 72.1 106 57.3 <0.001

no 149 34.2 70 27.9 79 42.7

House ownership yes 430 98.6 248 98.8 182 98.4 0.51

no 6 1.4 3 1.2 3 1.6

Car ownership yes 199 45.6 153 61.0 46 24.9 <0.001

no 237 54.4 98 39.0 139 75.1

		Total n = 436	Males n = 251	Females n = 185	p-value*
Age (yrs)	65–≤75	229	52.5	123	49.0	106	57.3	0.09
	>75	207	47.5	128	51.0	79	42.7
	mean±sd	75±6.2	75.4±6.1	74.4±6.2	0.11
Education (yrs)	0	32	7.3	10	4.0	22	11.9	<0.001
	1–6	305	70.0	171	68.1	134	72.4
	7–12	76	17.4	55	21.9	21	11.4
	>12	23	5.3	15	6.0	8	4.3
	mean±sd	6.1±3.5	6.7±3.4	5.4±3.6	<0.001
Marital status	married	330	75.7	214	85.3	116	62.7	<0.001
	unmarried/widower	106	24.3	37	14.7	69	37.3
Annual family income (euros)	<10000	321	73.6	181	72.1	140	75.7	0.60
	10000–20000	95	21.8	59	23.5	36	19.5
	>20000	20	4.6	11	4.4	9	4.9
Body Mass Index (Kg/m²)	<24.9	105	24.1	61	24.3	44	23.8	<0.001
	25.0–29.9	208	47.7	142	56.6	66	35.7
	≥30.0	123	28.2	48	19.1	75	40.5
	mean±sd	28.0±4.4	27.3±3.6	28.9±5.0	<0.001
Smoking	never	240	55.2	73	29.1	167	90.8	<0.001
	former	134	30.8	126	50.2	8	4.3
	current	61	14.0	52	20.7	9	4.9
Physical activity status^a	low	105	24.1	55	21.9	50	27.0	<0.001
	moderate	137	31.4	52	20.7	85	46.0
	high	194	44.5	144	57.4	50	27.0
Growing vegetables and fruits	yes	287	65.8	181	72.1	106	57.3	<0.001
	no	149	34.2	70	27.9	79	42.7
House ownership	yes	430	98.6	248	98.8	182	98.4	0.51
	no	6	1.4	3	1.2	3	1.6
Car ownership	yes	199	45.6	153	61.0	46	24.9	<0.001
	no	237	54.4	98	39.0	139	75.1

Results are presented as frequencies n (%), age, education and BMI as mean±sd. ^aBased on International Physical Activity Questionnaire (IPAQ). *P-values derived through Student’s t-test and Chi-square test for sex differences.

Adherence to the MD, daily food consumption and energy intake results, as estimate of FFQ are presented in Table 2. In particular, the mean of the MedDietScore of total population was 31.9±3.6, with significant sex differences (p < 0.001). A relatively small percentage of the participants, 16.7%, had high adherence to the MD with more males than females (p < 0.0001). Energy intake was 1678±412 kcal/day, with no sex differences. However, sex differences were observed in food groups; females had higher daily intake of milk and dairy products (p < 0.001), fruits and fresh juice (p = 0.04), vegetables (p < 0.001) than males, and lower daily intake of meat products, potatoes (p = 0.03) and alcohol intake (p,<0.001). No other differences were observed.

Table 2

MedDietScore, daily intakes (g/day) of indicated food groups, as estimate of FFQ and dietary variables in older adults, aged > 65 years in Crete, Greece (n = 436)

Dietary variable	Total	Males	Females	p-value*
	(n = 436)	(n = 251)	(n = 185)
MedDietScore (0–55)^a	31.9±3.6	32.9±3.4	30.6±3.4	<0.001
Highest adherence^b	16.7%	23.1%	8.1%	<0.0001
Cereals (g/day)	110 (86, 135)	108 (88, 133)	113 (82, 141)	0.35
Potatoes (g/day)	34 (34, 64)	34 (34, 73)	34 (24, 64)	0.03
Vegetables (g/day)	131 (100, 210)	124 (96, 198)	162 (108, 219)	<0.001
Fruits /fresh juice (g/day)	240 (120, 247)	170 (120, 248)	240 (128, 250)	0.04
Meat and meat products (g/day)	82 (61, 97)	83 (68, 98)	78 (52, 97)	0.03
Fish and seafood (g/day)	32 (20, 52)	32 (20, 52)	32 (20, 52)	0.76
Milk and dairy products (g/day)	216 (64, 402)	183 (54, 388)	372 (121, 415)	<0.001
Pulses, nuts and seeds (g/day)	77 (60, 77)	80 (64,107)	77 (57, 102)	0.16
Sugars and syrups (g/day)	34 (18, 74)	32 (19, 60)	36 (15, 79)	0.33
Energy intake (Kcal/day)	1678±412	1677±376	1681±456	0.92
Alcohol intake (g/day)	0 (0, 16)	15.6 (0, 21)	0 (0, 0)	<0.001

Results are presented as mean±sd, for the normally distributed variables and 50 (25, 75) for skewed variables. *P-values, sex differences are derived via the Chi-square test, student t-test for the normally distributed variables and via the Mann–Whitney U-test for skewed variables. ^aIn parenthesis are presented the minimum and maximum possible values of each component. ^bHighest adherence to Mediterranean Diet was defined according to highest tertile of diet score or 36–55 as referred by Panagiotakos and colleagues in Nutr Metab & Card Dis, 2006; 16 : 559-568.

The scores of SC, PCS and MCS are presented in Table 3, for the total population and by sex. The total SC score was 75 (68,80) with no sex differences. Important differences were found between genders in Participation in the Local Community (p = 0.009), Feelings of Safety and Trust (p < 0.0001), Family and friends Connections (p < 0.0001). The PCS score was 45 (37,52) with males reported higher than females (p < 0.0001). The MCS score for total population was 47 (40,54), with males reporting higher than females (p < 0.01). Sex differences were observed in the Bodily Pain (p < 0.0001), General Health (p = 0.005), Vitality (p = 0.002), Social Functioning (p < 0.0001) and Mental Health (p = 0.0001). No differences were noted in the physical and emotional roles.

Table 3

Score for total Social Capital and its dimensions, for the eigth dimensions of the Sf 36, Physical Component Summary (PCS) and Mental Component Summary (MCS), in older adults, aged > 65 years in Crete, Greece (n = 436)

	Total	Male 251	Female 185	P*
	Median (25–75)	Median (25–75)	Median (25–75)
SF-36 components
Physical Functioning	65 (40,85)	75 (50,95)	50 (35,75)	<0.0001
Role-Physical (RP)	63 (39,81)	63 (38,88)	63 (44,82)	0.71
Bodily Pain	62 (42,74)	64 (51,84)	61 (41,72)	<0.0001
General Health	50 (35,67)	52 (40,67)	47(30,62)	0.005
Vitality	56 (50,69)	63 (50,75)	56 (44,69)	0.002
Social Functioning	75 (63,100)	88 (75,100	75 (50,100)	<0.0001
Role-Emotional (RE)	58 (33,92)	58 (33,100)	58 (25,92)	0.113
Mental Health	70 (55,85)	75 (65,85)	65 (50,80)	<0.0001
Physical Health Summary	45 (37,52)	47 (39,53)	41(35,50)	<0.0001
Mental Health Summary	47 (40,54)	48 (42,54)	45(37,53)	<0.01
Social Capital score
Total Social capital (31–124)	75 (68,80)	74 (68,80)	75 (69,80)	0.555
Local community (12–48)	20 (18,23)	20 (18,22)	21 (19,23)	0.009
Safety/Trust (2–8)	6 (5,7)	6 (5,7)	6 (4,7)	<0.0001
Family-friends (2–8)	4 (3,5)	4 (3,5)	4 (3,5)	<0.0001
Tolerance of diversity (2–8)	4 (3,4)	4 (3,4)	4 (3,5)	0.065
Value of life (11–44)	33 (30,35)	33 (30,36)	33 (30,36)	0.341

*P-values, sex differences are derived via the Mann–Whitney U-test for skewed variables. The summary measures of PCS and MCS use norm-based scoring (mean = 50, standard deviation = 10).

The results of a linear regression when considering various participants’ characteristics, as significant factors for adherence of MD are presented in Table 4. In model 1 only sex was included and the results showed that males were significantly positively associated with higher levels of Med Diet Score, with 2.285 points (p < 0.0001). When in model 2, age was added, male was still significantly positively associated with higher level of Med Diet Score, (p < 0.0001) but age was not. In model 3, education (p = 0.530) and marital status (p = 0.039) were added, sex was still significantly associated with Med Diet Score (p < 0.0001). In model 4, where annual income (p = 0.299), and car ownership (p = 0.044) were added, sex was still significantly associated with Med Diet Score (p < 0.0001). In Model 5 where “growing vegetables and fruits” (p = 0.014) added, the sex was still significantly associated with Med Diet Score (p < 0.0001).

Table 4

Results (B unstandardized cofficients±SE), from regression analysis models that evaluate determinants of adherence Mediterranean diet in older adults, aged > 65 years in Crete, Greece (n = 436)

	Model 1	Model 2	Model 3	Model 4	Model 5
	B±SE, p	B±SE, p	B±SE, p	B±SE, p	B±SE, p
Sex	–2.285±0.329,<0.0001	–2.316±0.330,<0.0001	–0.072±0.350,	–1.869±0.368	–1.798±0.367
(0 = male,1 = female)			<0.0001	<0.0001	<0.0001
Age		–0.032±0.027,	–0.014±0.028,	–0.001±0.029,	0.007±0.029,
(years)		0.226	0.625	0.985	0.811
Education			0.031±0.049,	–0.009±0.053	–0.004±0.053,
(years)			0.53	0.866	0.933
Marital status			0.833±0.403,	0.574±0.414,	0.258±0.431,
			0.039	0.166	0.55
Annual income (Euros)				0.434±0.417	0.449±0.414,
(0=<10000, 1=>10000)				0.299	0.279
car ownership				0.784±00.388,	0.772±0.386,
(0 = no, 1 = yes)				0.044	0.046
Growing vegetables					0.900±0.365,
and fruits					0.014
(0 = no, 1 = yes)

4 Discussion

In this work we presented the rationale, design, baseline sociodemographic, dietary characteristics, social capital and health related quality of life scores of the MINOA study. The main finding of the MINOA study reported herein is that in older adults living in Crete, Greece, adherence to the MD was moderate with potential barriers being the low or moderate Social capital as well as PCS and MCS of the HRQL. Gender, car ownership and growing vegetables and fruits were significance predictors of adherence to Mediterranean Diet.

In particular, the MedDietScore was 31.9±3.6 falling in the range of moderate, 21–35 [23], with males showing higher score than females (p < 0.001). This observation in this population group and area is of particular interest because, although this study population is not the cohort of the Seven Countries Study, it was the adult population of this area in Crete in the late 1950 s, where the Mediterranean dietary pattern was first observed in the 7 Countries Study [6]. Another study (MEAL) conducted in Sicilians but in ages over 18 years, showed higher adherence in older groups compared to younger ones [59]. The characteristics of the Mediterranean dietary pattern are: high daily consumption of olive oil as the main source of fat, daily consumption of whole grains and nuts, fresh fruits, vegetables, legumes, low-to-moderate consumption of milk and dairy products, fish, low consumption of red meat and rare consumption of sweets and low to moderate consumption of wine [41]. According Real et al., the Mediterranean diet is a “Food pattern” that represents a set of foods and nutrients, with a positive impact on health. Also Mediterranean diet can be considered as a “Diet” because represents not only the food consumption but also truly a way of life of each individual and it considers other aspects such as culture, food production, society, economy, sustainability, culinary activities, conviviality, physical activity [60].

Adherence to this pattern was moderate herein, as reflected in the MedDietScore and in the pattern of consumption of food groups (cereals, potatoes, vegetables, fruits/fresh juice, meat and meat products, fish and seafood, milk and dairy products, pulses, nuts, and seeds, sugars and syrups and alcohol). The FFQ data of daily consumption of olive oil might not be accurate. However, research has shown [5] that in 40–45% of total energy intake was fat most of which came from olive oil. Sex differences were observed: females had higher daily intake of milk.

Similar results of adherence to the Mediterranean Diet were reported in previous studies. The MEDIS (MEDiterranean Islands) study showed that in Crete adherence to the MD was moderate, while older adults females had lower adherence than males (31.64±4.43 and 32.53±3.28, respectively) [3]. Another study in older adults in Athens, Greece showed sex differences, with lower MedDietScore for females (29.7±3.0) than males (30.7±3.4) [24]. Energy intake for males (1677±376 Kcal/day) reported herein deviates slightly from reports in a previous study (1782±419Kcal/day) conducted in the same area, in older adults who had survived from Cretan cohort of the Seven Countries Study [42]. Furthermore, sex differences were observed in PREDIMED-plus study that showed in Spanish adults with better adherence to the MedDiet were more likely to be women [58]. The reasons of the observed decrease and the moderate adherence to the Mediterranean Diet reported in the MINOA study and others remain unclear.

The second important finding of the MINOA study relates to our hypothesis of potential barriers that may explain deviations from the Mediterranean dietary pattern in older adults in Crete. We hypothesize that weak support (whether true or perceived) from family and community structures and weak functional physical and mental health constitute barriers to accessing, preparing and consuming foods that characterize the Mediterranean Diet. Clearly physical/physiological and psychosocial changes occur in older age.

Social support (whether true or perceived) from family and community structures, described by Total Social Capital Score, in the MINOA study was 75 (68,80) with no sex differences. Actual cut-offs of low scores are not available to date, therefore results are compared based on achieved mean score with regards to minimum (31) and maximum (124) values. Social Capital has been measured using various methods and scoring across countries and in different population groups, therefore, comparisons between SC in older adults populations may not be relevant. A study in adolescents must be mentioned as it was conducted in Crete, which shows that they have SC 72.4 (9.5) for male and 72.7 (8.9) for female, with no differences between genders [43].

Bolin et al [44] argued that SC decreases with aging most probably because personal interactions also decrease with age [45] thus attributing the decrease to social challenges directly affecting older adults, not just their communities [46]. For instance, social exclusion, social isolation, and loneliness are becoming emerging issues in later life, negatively affecting health, well-being, and social participation of older adults [47, 48]. Individuals that are frightened to move in their community, cannot fully participate in community life, and consequently are not able to secure benefits that may be available to them. Research has shown that the Internet can help address issues of social participation, connectedness, and well-being by providing communication opportunities, information and services (e.g., health-related information) that can facilitate activities of daily living, social participation, and active ageing [49]; however, this observation obviously applies to communities and individual that are able to use these means of communication and networking. Social participation may promote positive psychological states to enhance motivation for healthy diet behaviours [50].

Physical/Physiological and Psycological aspects of functional health of the population, the PCS and MCS of the HRQL, was norm-based scoring, as recommended [51, 52]. <span TMPID=“193” style=’color:black’>The present study showed low PCS and MCS score, for the total sample, and for each sex separately. Myint and colleagues defined PCS and MCS scores≥55 as good physical and mental health status [53]. Sex differences were found; higher males’ PCS and MCS scores may be responsible for better adherence to Mediterranean diet (it will be further discussed in our future work). Comparison of the MINOA study population with populations from other studies suggests that the MINOA study population has higher scores in PCS. For example in a study conducted in Athens, older adults aged over 65 years old had PCS 40.6 (38.8, 42.2) and MCS 48.2 (46.5, 49.8) [54]. Data from the Medicare Health Outcomes Survey, Cohort I Baseline [55], show similar results for people aged over 65 years old (PCS = 43, MCS = 52). Advanced age is associated with increasing health problems, which means a decline in HRQL. Also in the present study, males appeared higher physical activity than women, as opposed to another study, among older adults in Athens, where the women appeared more physically active [24]. Sociodemographic characteristics of our cohort are in accordance with previously published data [24]. The daily energy intake for males was lower than daily energy requirement by WHO [56].

As far as the socio-demographic data of MINOA study, it was showed that adherence to MD is linked with the marital status, according to previous research [57]. Gender, car ownership and growing vegetables and fruits were significance predictors of adherence to Mediterranean Diet. It is interesting to note that owing and using a car, in rural areas of Crete, where the study was conducted, is necessary for transportation in city centers, for purchasing/ transporting food commodities. The cultivation of vegetables and fruits, as part of a Mediterranean dietary pattern, ensures, also, their consumption. It must be pointed out that, in this study population, the annual family income of the majority was less than 10,000 euros. Growing their own fruits and vegetables can also help the family financially.

5 Conclusion

Older adults in a rural area of Crete had a moderate adherence to the Mediterranean diet. We hypothesised that barriers to access, prepare and consume foods that characterise the Mediterranean Diet may be linked to socioeconomic, physical and psychological factors observed in older age. In the study population car ownership and growing vegetables and fruits are significance predictors of adherence to Mediterranean Diet. The Social Capital as well as the Physical and Mental Components of Health observed in the population tested encourage further investigation of our hypothesis.

Funding

They have been no funding sources or grants.

Conflict of interest

The authors have no conflict of interest to report.

Footnotes

Acknowledgments

The authors thank the Mayor of MINOA Municipality, Mr Zacharia Kalogeraki, for the permission to carry out the study in the municipal structures of older adults. We also thank the employees of “KAPI” and “HELP at HOME PROGRAM” of MINOA Municipality, as well as Mrs Chrysavgi Galanaki for the support during the conduction of the study, Dr Ioanna Moschandrea, Dr George Kritsotakis, Dr Manolis Linardakis and Dr Thanasis Alegakis for valuable discussions on the study methodology and Mrs Nantia Boufachrentin for the proofreading of this article.

References

FAO. Mediterranean Food Consumption Patterns: Diet, Environment, Society, Economy and Health. A White Paper Priority 5 of the Expo Milan 2015; Feeding Knowledge Programme. Rome: Food and Agriculture Organization of the United Nations/International Centre for Advanced Mediterranean Agronomic Studies; 2015.

Da Silva

, Bach-Faig

, Raidó Quintana

, Buckland

, Vaz de Almeida

, Serra-Majem

. Worldwide variation of adherence to the Mediterranean diet, in 1961–1965 and 2000–2003. Public Health Nutr. 2009;(12):1676–84.

Tyrovolas

, Polychronopoulos

, Bountsiouka

, Zeimbekis

, Tsiligiani

, Papoutsou

, et al. Level of Adherence to the Mediterranean Diet Among Elderly Individuals Living in Mediterranean Islands: Nutritional Report from the Medis Study. Ecology of Food and Nutrition. 2009;48(1):76–87.

Garcia-Closas

, Berenguer

, Gonzalez

. Changes in food supply in Mediterranean countries from 1961 to 2001. Public Health Nutr. 2006;9(1):53–60.

Kafatos

, Verhagen

, Moschandreas

, Apostolaki

, Van Westerop

. Mediterranean diet of Crete: foods and nutrient content. J Am Diet Assoc. 2000;100(12):1487–1493.

Keys

, Aravanis

, Blackburn

, Van Buchem

, Buzina

, Djordjevic

, et al. Epidemiological studies related to coronary heart disease: characteristics of males aged 40–59 in seven countries. Acta Med Scand Suppl. 1966;460:1–392.

World Health Organization. A conceptual framework for action on the social determinants of health. Social Determinants of Health. WHO: Geneva; 2010.

Bourdieu

. The forms of capital. In Halsey AH, Lauder H, Brown P, Stuart Wells A, editors. Education: Culture, economy, and society Oxford, UK: Oxford University Press; 1997, p. 46-58.

Coleman

. Social capital in the creation of human capital. American Journal of Sociology. 1988;94:95–120.

10.

Putnam

. Bowling alone. The collapse and revival of American community. Simon and Schuster, editors. New York US: Touchstone Books; 2000.

11.

Woolcock

. The place of social capital in understanding social and economic outcomes. Canadian Journal of Policy Research. 2001;2(1):11–7.

12.

Kawachi

, Kennedy

, Glass

. Social capital and self-rated health: a contextual analysis. Am J Public Health. 1999;89(8):1187–93.

13.

Lindstrom

, Hanson

, Wirfalt

, Ostergren

. Socioeconomic differences in the consumption of vegetable, fruit and fruit juices. The influence of psychosocial factors. European Journal of Public Health. 2001;11:51–9.

14.

Addy

, Wilson

, Kirtland

, Ainsworth

, Sharpe

, Kimsey

. Associations of Perceived Social and Physical Environmental Supports With Physical Activity and Walking Behavior. American Journal of Public Health. 2004;94(3):440–3.

15.

Morgan

, Haglund

BJA

. Social capital does matter for adolescent health: evidence from the English HBSC study. Health Promotion International. 2009;24(4):363–72.

16.

Johnson

, Sharkey

, Dean

. Eating behaviors and social capital are associated with fruit and vegetable intake among rural adults. J Hunger Environ Nutr. 2010;5(3):302–15.

17.

De Silva

, McKenzie

, Harpham

, Huttly

. Social capital and mental illness: a systematic review. J Epidemiology Community Health. 2005;59(8):619–27.

18.

Souza

, Grundy

. Intergenerational interaction, social capital and health: Results from a randomised controlled trial in Brazil. Social Science & Medicine. 2007;65(7):1397–409.

19.

World Health Organization. WHOQOL-BREF: Introduction, Administration, Scoring and Generic Version of the Assessment; Programme on Mental Health. WHO: Geneva; 1996.

20.

Idler

, Benyamini

. Self-rated health and mortality: A review of twenty-seven community studies. Journal of Health and Social Behavior. 1997;38(1):21–37.

21.

Kaplan

, Goldberg

, Everson

, Cohen

, Salonen

, Tuomilehto

, et al. Perceived health status and morbidity and mortality: evidence from the Kuopio Ischeamic Heart Disease Risk Factor Study. Int J Epidemiol. 1996;25(2):259–65.

22.

Munoz

, Fıto

, Marrugat

, Covas

, Schroeder

. Adherence to the Mediterranean diet is associated with better mental and physical health. B J Nutr. 2009;101:1821–7.

23.

Panagiotakos

, Pitsavos

, Stefanadis

. Dietary patterns: a Mediterranean diet score and its relation to clinical and biolological markers of cardiovascular disease risk. Nutr Metab Cardiovasc Dis. 2006;16:559–68.

24.

Kanoni

, Dedoussis

. Design and descriptive characteristics of the GHRAS: the Greek Health Randomized Aging Study. Med Sci Monit. 2008;14:CR204–12.

25.

Pitsavos

, Panagiotakos

, Chrysohoou

, Stefanadis

. Epidemiology of cardiovascular risk factors in Greece: aims, design and baseline characteristics of the ATTICA study. BMC Public Health. 2003;3:32.

26.

World Health Organization.Weight gain recommendations include cut-offs for BMI according to theWHO standards. Available from: http://www.euro.who.int/en/health-topics/disease-prevention/nutrition/a-healthy-lifestyle/body-mass-index-bmi.

27.

Craig

, Marshall

, Sjostrom

. International Physical Activity Questionnaire: 12-country Reliability and Validity. Medical Science Sports Exercise. 2003;35:1381–95.

28.

Malisova

, Bountziouka

, Panagiotakos

, Zampelas

, Kapsokefalou

. Evaluation of seasonality on total water intake, water loss and water balance in the general population in greece. J Hum Nutr Diet. 2013;26:90–6.

29.

Paparrigopoulos

, Tzavara

, Theleritis

, Psarros

, Soldatos

, Yiannis Tountas

. Insomnia and its correlates in a representative sample of the Greek population. BMC Public Health. 2010;10:531.

30.

Malisova

, Bountziouka

, Panagiotakos

, Zampelas

, Kapsokefalou

. The water balance questionnaire: design, reliability and validity of a questionnaire to evaluate water balance in the general population. International Journal of Food Sciences and Nutrition. 2012;63(2):138–44.

31.

Davidson, Passmore. Human nutrition and dietetics, editors Passmore R. 8th ed. Churchill Livingstone; 1986.

32.

Katsiardanis

, Diamantaras

, Dessypris

, Michelakos

, Anastasiou

, Katsiardani

, et al. Cognitive Impairment and Dietary Habits Among Elders: The Velestino Study. J Med Food. 2013;16(4):343–50.

33.

Onyx

, Bullen

. Measuring social capital in five communities. J Appl Behav Sci. 2000;36:23–42.

34.

Kritsotakis

, Koutis

, Alegakis

, Philalithis

. Development of the social capital questionnaire in Greece. Res Nurs Health. 2008;31:217–25.

35.

Pappa

, Kontodimopoulos

, Niakas

. Validating and norming of the Greek SF-36 Health Survey. Qual Life Res. 2005;14(5):1433–8.

36.

Anagnostopoulos

, Niakas

, Pappa

. Construct validation of the Greek SF-36 Health Survey. Qual Life Res. 2005;14(8):1959–65.

37.

Walters

, Munro

, Brazier

. Using the SF36 with older adults: across-sectional community- based survey. Age Ageing. 2001;30:337–343.

38.

Ware

, Gandek

. Overview of the SF-36 Health Survey and the international quality of life assessment (IQOLA) Project. J Clin Epidemiol. 1998;51(11):903–12.

39.

Saris-Baglama

, Dewey

, Chisholm

, et al. Quality Metric health outcomes™ scoring software 4.5.User’ Guide. Lincoln, RI: Quality Metric Inc; 2011.

40.

Optum. SF-36 v2 health survey (license Agreement 27/1/2014).

41.

Willett

, Sacks

, Trichopoulou

, Drescher

, Ferro-Luzzi

, Helsing

, et al. Mediterranean diet pyramid: a cultural model for healthy eating. The American Journal of Clinical Nutrition. 1995;61(6):1402S–6S.

42.

Hatzis

, Papandreou

, Patelarou

, Vardavas

, Kimioni

, Sifaki-Pistolla

, et al. A 50-year follow-up of the Seven Countries Study: Prevalence of cardiovascular risk factors, food and nutrient intakes among Cretans. Hormones. 2013;12(3):379–85.

43.

Koutra

, Kritsotakis

, Linardakis

, Ratsika

, Kokkevi

, Philalithis

. Social Capital, Perceived Economic Affluence, and Smoking During Adolescence: A Cross-Sectional Study. Substance Use & Misuse. 2017;52(2):240–50.

44.

Bolin

, Lindgren

, Lindstrom

, Nystedt

. Investments in social capital—implications of social interactions for the production of health. Social Science & Medicine. 2003;56:2379–90.

45.

Hodgkin

. Participating in Social, Civic and Community Life: Are We All Equal? Australian Social Work. 2011;64(3):245–65.

46.

United Nations. World population aging. New York: United Nations; 2013.

47.

Cornwell

, Waite

. Social disconnectedness, perceived isolation, and health among older adults. Journal of Health and Social Behaviour. 2009;50(1):31–48.

48.

Edelbrock

, Buys

, Waite

, Grayson

, Broe

, Creasey

. Characteristics of social support in a community-living sample of older people: the Sydney Older Persons Study. Australasian Journal on Ageing. 2001;20(4):173–8.

49.

Barbosa Neves

, Fonseca

JRS

, Amaro

, Pasqualotti

. Social capital and Internet use in an age-comparative perspective with a focus on later life. Plos one. 2018;13(2):e0192119. doi: org/10.1371/journal.pone.0192119.

50.

Sun

, Liu

, Webber

, et al. Individual social capital and health-related quality of life among older rural Chinese. Ageing Soc. 2015;1:1–22.

51.

Ware

, Kosinski

. SF-36 Physical and Mental Health Summary Scales: A Manual for Users of Version 1. 2nd Edition. Lincoln, RI: QualityMetric, Inc; 2001.

52.

Gandek

, Sinclair

, Kosinski

, Ware

. Psychometric Evaluation of the SF-36 Health Survey in Medicare Managed Care. Health Care Financ Rev. Summer. 2004;25(4):5–25.

53.

Myint

, Welch

, Bingham

, et al. Fruit and vegetable consumption and self-reported functional health in men and women in the European Prospective Investigation into Cancer –Norfolk (EPIC –Norfolk): a population-based cross-sectional study. Public Health Nutrition. 2007;10(1):34–41.

54.

Pappa

, Niakas

. Assessment of health care needs and utilization in a mixed public-private system: the case of the Athens area. BMC Health Services Research. 2006;6:146.

55.

Gandek

, Sinclair

, Kosinski

, Ware

. Psychometric Evaluation of the SF-36 Health Survey in Medicare Managed Care. Health Care Financing Review. 2004;25(4):5–25.

56.

FAO/WHO/UNU. Human energy requirements. Report of a Joint Food and Agriculture Organization of the United Nations/World Health Organization/United Nations University Expert Consultation: Rome, 17–24 October 2001. FAO food and nutrition technical report series: 2004; p.103.

57.

Leone

, Battezzati

, De Amicis

, De Carlo

, Bertoli

. Trends of Adherence to the Mediterranean Dietary Pattern in Northern Italy from 2010 to 2016. Nutrients. 2017;9:734.

58.

Álvarez-Álvarez

, Martínez-González

MÁ

, Sánchez-Tainta

, Corella

, Díaz-López

, Fitó

, Vioque

, Romaguera

, Martínez

, Wärnberg

, López-Miranda

, Estruch

, Bueno-Cavanillas

, Arós

, Tur

, Tinahones

, Serra-Majem

, Martín

, Lapetra

, Más Fontao

, Pintó

, Vidal

, Daimiel

, Gaforio

, Matía

, Ros

, Ruiz-Canela

, Sorlí

, Becerra-Tomás

, Castañer

, Schröder

, Navarrete-Muñoz

, Zulet

MÁ

, García-Ríos

, Salas-Salvadó

, Díez-Espino

, Toledo

. Adherence to an Energy-restricted Mediterranean Diet Score and Prevalence of Cardiovascular Risk Factors in the PREDIMED-Plus: A Cross-sectional Study. Revista Espanola de Cardiologia (Engl Ed). 2019;72(11):925–34.

59.

Marventano

, Godos

, Platania

, Galvano

, Mistretta

, Grosso

. Mediterranean diet adherence in the Mediterranean healthy eating, aging and lifestyle (MEAL) study cohort. International Journal of Food Sciences and Nutrition. 2018;69(1):100–7.

60.

Real

, Queiroz

, Graça

. Mediterranean food pattern vs. Mediterranean diet: a necessary approach? International Journal of Food Sciences and Nutrition. 2020;71(1):1–12.