INTRODUCTION:

Non communicable diseases (NCDs) can be defined as a wide spread group of diseases those are chronic in nature, progress gradually over the years and the leading causes of disabilities, morbidity and mortality among the adult population across the world. Lifestyle disease is also not a single disease but a diverse group of different non communicable diseases which are the by- products of our recently adopted fast paced modern lifestyle^1-2.

Thus, lifestyle diseases are the diseases, resulting from the way people live their day to day lives, the habits they adopted through the course of modern living that take them away from physical activities and healthy eating and pull them towards sedentary routine, accompanied with unhealthy eating and habits which in turn lead to the development of certain non-communicable diseases^3-4.

According to World Health organization (WHO 2018), 71% of all global death is attributed to NCDs and unfortunately, among all ‘premature death’ (death between the age group- 30 to 69 years) resulting from NCDs, 85% occur in middle- and low-income countries. Thus, the disease which used to be the health burden for the economically developed countries in the past now has become major threat to the blooming economy as well as to poor health system for those economically backward nations which have already been struggling against undernutrition related problems. WHO reported (2015) that every year NCDs bring about almost 5.8 million deaths in India and one out of four Indians has the chance of ‘premature death’ from different NCDs. Report from National Health Portal of Ministry of Health and Family Welfare, Government of India (2019) on NCDs revealed a marked epidemiological transition over the last two decades where in the year 1990 NCDs contributed to 30% of all disease burden in India dismally it turned into 55% in 2016.

NCDs result from the interplay between one’s genetic make-up, environmental, behavioral and physiological factors. As per WHO all the risk factors have been grouped into three main classes-1.non-modifiable, 2. modifiable and 3. metabolic risk factors; the non-modifiable factors are age, sex, race and family history; modifiable factors are typically the behavioral factors like use of tobacco, alcoholism, physical inactivity and unhealthy diet characterized by high fat and sodium intake and low consumption of fruits and vegetables. And these factors interacting with each other, further lead to metabolic changes in body like high blood pressure, overweight or obesity, hyperglycemia and hyper lipidemia and consequently result to the prognosis of NCDs^2,5-9.

Like other low- or middle-income countries, India is facing the ‘double burden of nutrition’; urbanization, industrialization and subsequent economic growth in India in twentieth century caused a rapid demographic transition, socio-economical changes, put people on sedentary lives and a shift towards ‘western diet’ from the traditional Indian diet which have been observed even in rural India, have pulled up the economic burden of our country to combat NCDs^10-14. WHO has developed STEP instruments (known as STEP wise approach to surveillance) to accumulate data regarding NCDs risk factors, evaluate and monitor them country wise across the world and the principal six risk factors those WHO addressed are unhealthy diet, physical inactivity, tobacco and alcohol consumption, obesity, elevated blood glucose and blood pressure^15-16. Peters et al. (2019) have carried out an extensive systemic review and concluded that unhealthy diet and physical inactivity are the strongest lifestyle risk factors to be highly associated with elevated evidences of diabetes, cerebro or cardio vascular diseases, cancer and dementia³. Fact sheet from National Family Health Survey (NFHS-4) 2015-16 by Ministry of Health and Family Welfare (Government of India) reported that among men belonging to 15-54 years of age, 18.9% were overweight or obese, 8% and 3.9% had blood sugar level >140 mg/dl and >160mg/dl respectively and 10.4% was mild, 2.3% was high and 0.9% was reported as very high hypertensive and these values in all cases were higher than their women counterparts (except in overweight or obesity- 20.6% in women), indicating Indian adult male are more ‘at risk’. And urban males were more prevalent in all mentioned groups than rural males.

Data regarding the two most influencing lifestyle factors- dietary pattern and physical activity among the already overweight or obese male who are more prevalent for NCDs and their comparison between rural vs. urban area in West Bengal is very limited. Those who are already obese but still have not been clinically diagnosed are more prone to get sudden hit of such diseases. Thus, the aim of this present study is to determine the dietary and physical activity pattern of those subjects (obese male) from rural and urban part of south Bengal and to find if there is any difference regarding these two factors; also, to measure the anthropometric parameters to predict the severity and risk of diseases amongst them.

MATERIALS AND METHODS:

A community based cross-sectional study was done on selected parts of Hooghly district. Urban areas were chosen from municipal areas and rural areas were represented by selected villages from gram panchayat of Community Development Blocks of that district. The subjects from the households of those areas were selected by systematic random sampling based on inclusion and exclusion criteria of the study.

Inclusion criteria:

All the study subjects were Bengalee (Hindu) male with age between 20-50 years, all the individuals were having BMI between 25- 30kg/m² but, they were free from any diagnosed chronic diseases. They never use any form of tobacco and alcohol. Total 150male subjects were chosen randomly for the study, out of which 75 were from urban setting and 75 were from rural background.

Exclusion criteria:

Non ambulatory or physically or mentally challenged persons were not included in this study. Those who are suffering from clinically diagnosed diseases and are on weight reduction therapy, underwent any medical surgery or consuming certain medication like anti-hypertensive, anti-depressant, steroids or others were excluded for this study.

Socio-demographic information:

General information regarding name, age, sex, religion, ethnic group, residence, education, occupation, marital status, family income and family size was collected. Socio economic classification was done using modified B.G. Prasad socio-economic scale 2019¹⁷.

Dietary information:

Multiple, non-consecutive, 24-hour recall method was used to collect data. Data was collected avoiding the fasting and festive days, dietary habits on weekend and week days were also considered. Standardized and locally suitable utensils were used during conversation. Respondents were asked to recall all the foods or beverages consumed on previous day, starting from the breakfast. Meals eaten outside were also recorded along with the portion size. Mean consumption of various nutrients and foods belonging to different food groups were assessed using Diet Cal software (based on nutritive value of Indian foods)¹⁸.

Physical activity:

Global Physical Activity Questionnaire (GPAQ) developed by WHO has been used to collect information regarding physical activities in three domains i.e., work, travel and recreation. MET scores (Metabolic Equivalents) of each domain, sub-domains and across all domains were calculated, where 4 METs and 8 METs are for at least 10 minutes time spent at a time in moderate and vigorous activities respectively^19-20.

Anthropometric Measurement:

Body weight, height, waist circumference (WC) and hip circumference (HC) were measured using standard protocols and instruments. Body Mass Index (BMI) was derived by dividing body weight (kg) by height (in meter squared). BMI is used to grade obesity. Waist to hip ratio (WHR) and waist to height ratio (WHtR) were calculated as well^21-22.

Definitions used in study:

Unhealthy diet: Diet with excess calorie, saturated and trans fat, sugar and salt but low in whole grains and legumes, fruits and vegetables are considered as unhealthy diet⁷.

Physically active and inactive:

Global recommendation of physical activity by WHO (2018) for adults is 150 minutes moderate intensity or 75 minutes vigorous intensity physical activity or an equivalent combination of both the vigorous and moderate intensity activity which would meet up at least 600 MET-minutes per week. Based on MET-minutes physical activity has further been classified into 3 groups:

1. Physically inactive (MET-minutes<600 in a week)

2. Active (MET-minutes 600-1200 in a week)

3. Highly active (MET-minutes >1200 in a week)¹⁹.

Obesity:

For Asian-Indian if BMI is ≥25kg/m² then the condition is obesity. BMI indicates generalized obesity whereas abdominal obesity is referred by WC ≥90cm for male. WHR ≥0.90 for male is also indicator for abdominal obesity. And cut off value of WHtR, another predictor of risks associated with adiposity is 0.5^23-24.

Statistical analysis:

Descriptive statistics like mean, standard deviation (SD) was done and to compare the mean values between the groups two tail, unpaired t-test was performed. When p value was<0.05, difference was considered as significant²⁵.

RESULT:

Among all the rural study population (n=75) 35 subjects (46.7%) belong to 20-35 years age group and 40 (53.3%) falls in 36-50 years age group whereas it is 36 (48%) and 39(52%) respectively for their urban counterparts (n=75). The mean ±SD age was 35.4±8.9 and 35.7±9 in rural and urban groups respectively.

Table: 1 describes the socio-demographic profile of rural and urban study groups. Table:2 depicts the dietary intake profile (Mean±SD) of both rural and urban study population. Consumption of calorie (kcal), dietary fiber (gm) and different food groups (gm) have been evaluated and compared between both the groups.

Table 1

Variables	Rural (N=75)		Urban (N=75)
Variables	No	%	No	%
Marital status
ever married	63	84	60	80
Unmarried	12	16	15	20
Educational status
Primary schooling or less	14	18.7	3	4
High schooling or above	61	81.3	72	96
Occupation
Officers/ professionals	9	12	22	29.3
Self-employed/medium/ small business person/cultivator	11	14.7	17	22.7
farm/ factory/construction or other labour	29	38.7	14	18.7
other unskilled manual	15	20	13	17.3
student/ unemployed	11	14.7	9	12
Socio economic status
Upper	4	5.3	16	21.3
Upper-middle	19	25.3	37	49.3
Middle	27	36	11	14.7
Lower-middle	16	21.3	7	9.3
Lower	9	12	4	5.3

Table 2

Average Nutrient consumption
Variables	Rural (Mean ±SD)	Urban (Mean ±SD)	Level of Significance (P≤0.05)
Calorie (Kcal)	2410.18 ±172.56	2505.09±199.2	0.002
dietary fibre (gm)	22.89± 7.05	18.93±4.64	0.000
Consumption of food groups
Whole grain +refined cereals (gm)	400.93± 13.46	408.98±18	0.003
pulses (gm)	33.88 ±9.04	28.86±4.93	0.000
Egg/meat/fish/poultry (gm)	29.87± 11.59	34.19±11.8	0.02
Dairy products (gm)	75.7± 26.29	90.47±16.82	0.000
root & tubers (gm)	110.67 ±31.84	111.93±17.06	≥0.05
Green leafy vegetables (gm)	29.71 ±13.18	20.2±9.75	0.000
Other vegetables(gm)	83.13±10.83	57.65±22.1	0.000
Fruits (gm)	25.34±9.32	28.51 ±8.93	0.03
Visible fats & oils	40.5± 9.32	44.66±8.16	0.004
Nuts& oilseeds(gm)	3 ±1.45	2.86±1.24	≥0.05
Added sugar (gm)	32.87 ±6.3	36.19±7.47	0.003
Added Salt (gm)	9.69 ± 1.43	9.5±1.44	≥0.05

Mean percentage of energy coming from different nutrients in both rural and urban groups have been represented in the following chart: 1.

The physical activity profile of both the groups and their differences in various domains were also calculated. Depending on MET value calculated 52% people was physically inactive in rural area and 58.7% was in urban area (MET value <600). 32% and 16% of rural male and 34.6% and 6.7% urban male were active and highly active respectively. Among rural study group, people mostly were inactive in recreation or leisure domain (57.3%) whereas in urban group most of them were inactive in both the work and recreation domain (61.3%) and least inactivity was observed in travel domain for both groups (33.3%-rural and 49.3% urban).

Mean time spends (minutes) on different activities/ day on various domains among both groups was also determined. Mean time/day spends on work domain (vigorous and moderate activity) were 23.1 and 40.4 minutes for rural group and 15 and 24 minutes for urban group respectively. There was a significant difference in mean time spent in travel domain (moderate activity) between rural and urban groups (12.8 minutes in rural and 8 minutes in urban/ day, p value was 0.01). Significant differences were found in vigorous and moderate recreation domains between these groups (6.7 minutes/ day in vigorous and 7.1 in moderate leisure physical activities in rural whereas it was 2.2 minutes and 5.03 minutes accordingly for urban males. The mean sitting time/day was 280 minutes for rural and 302.3 for urban males and difference was insignificant [Table 3]. The anthropometric profile of both rural and urban male has been shown in the following table [Table-4] and presented as mean ± SD and significance difference (if any) between the groups. Mean body weight, BMI and WHR were significantly higher amongst urban males where no significant difference was found regarding WC and WHtR between both groups.

Table 3:

Mean time spend on different activities/day (Mean ±SD) and level of significance
Activity	Domain	Subjects
Activity	Domain	Rural	Urban	Level of Significance (≤0.05)
VIGOROUS	WORK	23.1±50.6	15±57	≥0.05
VIGOROUS	RECREATION	6.7±28.2	2.2±7.2	0.000
MODERATE	WORK	40.4±74	24±63	≥0.05
	TRAVEL	12.8±14	8±8.6	0.01
	RECREATION	7.17±14.1	5.03±8.02	0.0001
SITTING		280±82.7	302.3± 98.1	≥0.05

Table 4:

Anthropometric profile of rural and urban subjects (Mean ±SD)
Variables	RURAL	URBAN	Level of significance <0.05
Body weight (kg)	79.7±5.9	82.3±5.8	0.006
BMI (kg/m²)	27±1.3	27.6±1.6	0.02
WC (cm)	98±3.6	99.1±3.8	≥0.05
WHR	0.98±0.03	0.99±0.02	0.003
WHtR	0.57±0.02	0.57±0.02	≥0.05

DISCUSSION:

In this study, authors have observed the pattern of dietary intake, physical activity and anthropometric profile as indicators of obesity related cardio-metabolic risks and their differences between the rural and urban adult (age- 20-50 years) obese (BMI 25-30kg/m²) male samples from selected study areas.

Dietary pattern which is unveiled in our study is quite distressing, where almost more than half of the subjects in both groups are physically inactive and all are obese, their mean consumption of calorie (kcal) are far above than the recommendation for sedentary male 2110 kcal (Recommended Dietary Intake for 2020)²⁶. It indicates positive energy balance among the subjects who are living sedentary lives with much calorie intake.

Changed dietary pattern even in rural India which is a consequence of rapid urbanization and demographic transition, is rich in calorie, excess fat, added sugar but with low fruits and vegetables and reduction in whole unprocessed grains. This trend has been noticed in many studies in India which have revealed that high consumption of snacks, processed and fast foods, aerated drinks, sweetened beverages are elevating the risks of NCDs among them even from childhood^27-30.

Our study also finds similarity with above trends. Overall consumption of calorie, visible fats, added sugar and dietary salt is truly alarming for both the study groups. And this is due to presence of faulty snacks, processed, ready to eat or cook foods or sweet beverages in diet. In this study, we observed consumption of pulses, dairy products; all vegetables (excluding potato), fruits and nuts are drastically low in both groups. Potato was the principal product in root and tubers group and among all vegetables this was found to be consumed in excess in bengalee population in both the study groups. It is further emerged that mean consumption of cereals is high in both groups and animal protein is low even in urban group.

Dietary data which was analysed, covering all four regions in India by Indian Council of Medical Research (ICMR) and National Institute of Nutrition (NIN) which reported in 2020, that mean consumption of certain food groups like pulse, dairy products, nuts and vegetables are less in both the urban and rural Indian adult’s diet irrespective of age, sex and region³¹.Report of National Nutrition Monitoring Bureau (NNMB) in 2017 on urban diets and risks of NCDs also mentioned presence of bulk of cereal and starchy roots in diets of West Bengal³². Another survey in Durgapur, West Bengal by Mukherjee et al. 2018 noted that both in rural and urban area of Durgapur, the food group mostly eaten is starchy staple and then oil and fat-based products. Consumption of dark green vegetables and animal protein were significantly higher in rural than urban group³³.

The finding regarding differences of dietary profile between rural-urban sectors is similar with the study done on rural; rural to urban migrants and urban adults (both male and female) in four cities of India (Nagpur, Lucknow, Hyderabad and Bangalore) in 2011, where mean calorie consumption by rural male was lower than urban. But the total calorie consumption by those groups was much higher than our study, which may be due to the participation of subjects from industrial zones. The percentage of energy deriving from macronutrients in rural vs. Urban was (63.3% vs. 62.4% from carbohydrate, 24.8% vs. 25.9% from fat, 7.4% vs. 7.7% from saturated fat, 11.3% vs. 11.5 from protein; almost similar with our result (66.7% vs. 63%, 24.6% vs. 26.2%, 6.58% vs. 8.03% and 9.3% vs. 11.2% respectively for rural vs. Urban subjects). Though intake of fruit, sugar, dairy and animal protein consumption was noted as higher in urban group but the mean vegetable intake was also higher in that group, which differs from our study³⁴.ICMR-NIN (2020) survey on different regions and their rural and urban differences reported as ‘what India eat’ showed a trend of lower consumption of legumes, nuts, vegetable and fruits and higher intake of cereal across the country. Low intake of fruits and vegetables and dairy products are also mentioned as a cause of prevalence of hypertension and diabetes. ICMR-NIN has developed ‘My Plate for the Day’ as a set of dietary recommendation to cut down risks of NCDs and the recommendations are ≤40% energy from cereal group (equivalent to 240 gm cereals), 17% energy from pulses and other animal protein (equivalent to 90 gm/day), <30% energy from fat, 350 gm of all vegetables excluding potato, 150 gm of fruits, 300 ml milk or equivalent dairy products, 30 gm nuts/ day. As compared to this recommendation our result shows dietary pattern of both group is completely unhealthy and must be associated with raised metabolic risks³¹.Low fruit and vegetables intake and high dietary salt consumption have considered as the dangerous dietary risks among many other dietary factors, so WHO STEP study to assess NCDs risk has introduced these two points³⁵. Many such surveys have been done in different states or the rural-urban difference among those states of India to surveil prevalence of NCDs. Among these studies Tripathy et al. found no difference in mean serving of fruits and vegetables/ day in rural (2.3) and urban (2.4) and dietary salt intake was 9.5 gm for urban and 17.7 gm for rural, which was significantly high. A study in Tamilnadu showed only 0.1% of adult male and 0.6% of rural male are taking either greater or equivalent to five serving of fruits and vegetables as referred by WHO^36-40.

Physical activity pattern, another strong determinant of lifestyle diseases has been monitored in our study groups. According to MET scores more than half of the total subjects in both rural-urban groups identified as physically inactive (58.7% in urban and 52% in rural). No difference was found in work domain between both groups due to modern working environment. In Travel domain, rural group showed significantly higher time spent than urban group, which may be because of more cycling, walking as a mean for travel in rural area. Mean time spent during leisure is low for both groups but still rural males are more involved in moderate and vigorous physical activities like household chores, gardening or some sorts of outdoor games observed in young adults. But it is to be mentioned that though mean time spent on recreational activities is higher in rural group but 57.3% which means more than half of total rural sample is inactive in that particular domain whereas it is 61.3% in urban.

A lot of studies have been carried out on different time in different states to monitor the physical activity pattern of those residents and their risks with hypertension, diabetes, obesity, metabolic syndrome, cardio vascular or all other NCDs. And it is emerged from almost all studies that Indian whether urban or rural resident is moving towards sedentary living. ICMR (Anjana et al. 2014) published a report on the trend of physical activity and inactivity among Indians and selected four states (Chandigarh, Tamilnadu, Jharkhand and Maharashtra) those represented four regions (north, south, east and west) of the country and showed that among male 13.7%, 31.9% and 54.4% were highly active, active and inactive respectively. So, our finding is very much similar with this study, though it was far above the global prevalence of physical inactivity (21.4%)⁴¹.Many studies in India also compared physical activity pattern between rural and urban areas of different states, where some of them showed no such significant difference exists and few others observed higher physical inactivity within urban groups. Anjana et al. 2014, in this study showed physical inactivity prevalence between urban vs. Rural males were 62.8% vs. 54% in Chandigarh, 62.2% vs. 43.9% in Maharashtra, 64.1% vs. 48.2% in Tamilnadu, and 44.4% vs. 13.8% in Jharkhand. Another study in Puducherry represented 49.7% prevalence in urban areas. Physical inactivity was 61.4% found from a study by Bhattacharjee et al. (2014) in Siliguri among urban population in West Bengal^{41, 42-43}.Mean time spent on different domains/ day in different regions have also been studied. ICMR-INDIAB study shows overall spending of time over different domains across four regions for males are 55.8 minutes/day in vigorous to moderate activity in work domain, 15.7 minutes/ day in travel domain, and 19.6 minutes/ day in leisure domain, which is comparable with our results⁴¹.Study in rural Kerala (2015) showed males spent mean 51.8 minutes in work domain, 15.9 minutes in leisure and 15.7 minutes in travel in a day. But in our study, we found, rural males are spending 23.1 and 40.4 minutes in vigorous and moderate activity respectively, 12.8 minutes for travel and 6.7 minutes for vigorous and 7.2 minutes on moderate leisure activities in a day. Study on physical activity between rural and urban area in Tamilnadu reported urban people are spending more time on leisure activities than rural, which is contrasting with our result. But in other two domains rural are spending much time which is same as our report. Mean time spend actively was less in our study, which may be due to our subject selection who are already obese^44-45. Many other studies have shown association between physical inactivity, faulty dietary habit among obese or overweight population in India as well^46-47.

We selected the obese subjects in our study. So, the anthropometric parameters related to adiposity would be naturally high as adiposity causes altered physiological health status including reproductive health^48-49. But as these people are not clinically diagnosed so here, we used the anthropometric parameters as predictors of cardio-metabolic risk factors. And those parameters are alarming (mean BMI- 27 to 27.6 kg/m²; WC- 98 to 99 cm; WHR- 0.98 to 0.99 and WHtR 0.57 among rural and urban group respectively) and we may predict cardio metabolic risks for study groups. Several studies have been done on such indices to use them as the strong predictors of hypertension, insulin resistance, diabetes, dyslipidemia, metabolic syndrome in different countries on different people. Difference in race, ethnicity or region may differ with the cut off regarding anthropometric indices but their sensitivity with risk of NCDs is independent^50-59.

CONCLUSION:

From the above study we can conclude that dietary pattern is unhealthier in urban obese male group with less physical activity than rural obese male counterpart. These two factors are strong predictors for NCDs determined by World Health Organization. Though elevated indices of anthropometry like BMI, WC, WHR or WHtR are strong indicators for severe health risks in study groups but still bio-chemical and cardio vascular parameters should assess in further study. Intervention programs through proper lifestyle management like maintaining healthy diet and having some exercise or other physical activity can produce better result which could be done as a part of our future research projects.

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Received on 12.06.2021 Modified on 15.08.2021

Research J. Pharm. and Tech 2022; 15(9):3924-3930.

DOI: 10.52711/0974-360X.2022.00657