In our study, two major behavioural factors like unhealthy diet and physical inactivity of NCDs along with anthropometric parameters among the obese Bengalee women (20–50 years of age) from selected parts of both rural and urban groups were studied. And the overall view that has been emerged is utterly dreadful.
Like other developing countries, India has been a witness to dietary transition as a consequence of urbanization, industrialization and globalization. Changed dietary pattern has been observed even among the rural residents; easily accessibilities to fast foods/junk foods/ready to cook or eat foods have displaced the traditional food consumption pattern in India(18–20).Numerous studies have been done on changed dietary pattern of Indians and all of these noted that consumption of dietary fibre, fruits and vegetables are gradually decreasing whereas intake of visible fats and added sugar are escalating rapidly (21).
In this study, researchers have also found such similarities in the dietary pattern of both rural and urban groups which was characterised by low intake of fruits, vegetables but high intake of dietary fat and sugar. Consumption of plant and animal protein was lower than the recommended value in both groups. Urban obese group was having more animal protein, dairy products, fruits, visible fat and oil and added sugar than rural group whereas rural group was consuming more pulses, green leafy and other vegetables and nuts and oil seeds. And these differences were significant, on the other hand there was no such differences regard to the cereals, root and tubers which was mainly potato and in salt consumption between the both groups.
Our study revealed that most of the daily energy is coming from carbohydrate, a reason behind increasing diabetes in India and consumption of poor amount of vegetables and fruits and increased amount of cereals indicate that those subjects’ diets are greatly unhealthy (22–25).
Poor consumption of dairy products and animal protein especially in rural group which is observed in this study differs from the observations of Shetty (2002) (21).But the study made by Sharma et al.(2020) that compared Indian diet considering all the districts and the rural-urban areas in India with the recommendation made by Eat-Lancet, mentioned that calorie intake from protein from both the animal and plant sources is quite below the referred range and in rural diet only 6% of energy comes from protein, which is similar to our findings. This study also put forward that low intake of whole cereals, fruits and vegetables except potato and high intake of fat, added sugar and salt is the cause behind the escalating NCD burden of India (26).
A cross-sectional study on rural, urban and migrants in the industrial areas of four large cities in India found that % of energy from nutrients in both rural and urban females were 63.9% and 62.6% from carbohydrate, 10.7% and 11.3% from protein, 24.9% and 26.4% from fat and 7.3% and 7.9% from saturated fat respectively. Except carbohydrate all the values were higher than our study. But in connection to food group consumption showed similar results i.e. fruits and vegetables, dairy products and meat intake were significantly higher in urban female group than the rural group (27). Rural-urban difference in dietary pattern among ever married women in Orissa, pointed out higher percentage of women (age-15-49 years) with BMI > 18.5 from urban area were consuming fruits, green leafy and other vegetables, dairy products and animal protein than their rural counterpart. And also more percentage of urban female was vegetarian than rural which may be a reason behind their high consumption of vegetables (28). Dietary and nutrient intake by urban females (mean age 45.8 ± 9.8) in a North Indian study noted urban diet was low in cereal, pulses, fruits and vegetables but rich in saturated fat, tran fat and total fat than the recommended values (29). ICMR-NIN (2020) reports on ‘what India eats’, showed that almost 97% in rural and 69.8% in urban region consume more than recommended amount of cereals and overall poor intake of fruits and vegetables and dairy products irrespective to sex and regions of India is the reason behind the elevated events of diabetes and hypertension accordingly. It also remarked that refined cereals and carbohydrates are contributing highest amount of energy to meet their daily energy needs (22). Another study in south India by Sowmya et al. (2016), where 58% of participants were women, aged over 20 years, unveiled similar findings that most energy is coming from cereal group and carbohydrate and less from fat and also noted low intake of fruits, vegetables, dietary fibre, tubers and sugar (30). Survey conducted by National Nutrition Monitoring Bureau (NNMB) 2017 on urban male and females in all states, concluded that people of both sexes consume a bulk amount of cereals and lower amount of fruits, vegetables and dairy products which was prevalent in all states but in few states including West Bengal tuber (mainly potato) consumption was very high (31). Many STEP-studies have been done in various parts of India on both sexes of rural and urban areas in different times which also put forward similar findings in terms of consumption of fruits and vegetables (as selected indicator of NCDs) and amongst almost all cases rural intake of fruits and vegetables were less than urban (32–35).
Physical activity which has been measured in this study, another behavioural risk factor for lifestyle diseases was also not satisfactory as well. More than half of all subjects, in both groups were inactive i.e. MET score < 600. Urban obese women were more inactive (78.7%) than rural group (64%). Only 4% among rural subjects were only highly active whereas it was 0 in urban. This observation may be due to our selection of only obese female group. Across all the domains, urban subjects were mostly inactive in occupational domain whereas highest percentage of inactivity among rural subjects was found in recreational domain. Mean time/day spent on different sub-domains were also recorded and expressed that rural group spent only 9.6 minutes in vigorous work, 16.6 minutes in moderate work whereas it were 1.4 minutes and 6.5 minutes respectively for urban group. In travel domain it was 8.9 minutes and 5 minutes for rural and urban group respectively and was significantly higher in rural group but regarding recreation in both the sub domains (vigorous and moderate) no such differences was noted. Age group wise (20–35 years & 36–50 years) participation in leisure activity was measured and emerged that older age group was less active in leisure among both the groups.
Ample researches have been done on physical activity pattern on both the sexes among adults in different regions covering both the rural-urban parts across India and most of them specified more physical inactivity amongst urban females than their rural counterparts, which also goes with our observation. ICMR-INDIAB (2014) studied on different states and rural-urban areas there in, showed 59.6% of rural female and 71.2% of urban females were inactive whereas only 12.6% and 5.8% were highly active from selected rural and urban India respectively. Among urban areas, highest percentage of women from Chandigarh were physically inactive (83.2% in urban and 75.1% in rural) and least from Jharkhand (55.3% from urban and 44.2% from rural). And mean time spent/day on moderate to vigorous physical activity (MVPA) among all domains indicated that females in Tamilnadu spent least time in work domain (25.7 minutes) and highest was in Maharashtra (43.5 minutes), whereas in travel and leisure domains Tamilnadu spent lowest time in a day (11.6 minutes and 12.7 minutes respectively). This study also showed activity in recreational domain gradually decreases with increase in age and was alike our report (36). Study of Shah and Mathur (2010) surveyed the prevalence of cardio vascular risk factors in India based on ICMR surveillance reports and noted that higher number of urban females were more inactive in work and travel domain whereas rural females were more inactive in leisure domain (37). Another South Indian study revealed that only 14% urban females were highly active whereas 50.7% females were engaged in the same from rural area (38). Mathew et al. (2009) in their study in South India on difference of physical activity among women in rural and urban areas produced the similar results as well (39).Tripathy et al. (2016), studied rural-urban differences regarding diet, physical activity and obesity on both male and female in North India (Punjab) and unveiled that 27.4%, 24.1%, 94.3% urban females and 24.7%, 32.8%, 95.2% of rural females were inactive in work, travel and recreational domain accordingly. But there no significant differences were found between rural and urban females regarding daily mean time spent on three domains and that is contrast to our study but such result might be due to selection of areas or the subjects (40). And that result also differed from other studies in South India, like Devamani et al. 2019 showed inactivity of urban females were (70.8%) far above than rural group or the report of Newtonraj et al. (2019) which again noted lesser percentage of physical inactivity in rural females than urban which was 22.5%, almost comparable to the prevalence of global physical inactivity i.e. 27.5% (41–43).
The subjects those who were chosen from both the rural and urban areas, were obese i.e. BMI > 25 kg/m2. So the mean value of various anthropometric indices measured would definitely be higher when compared to general groups. Though we haven’t studied or compared obesity prevalence between selected rural-urban females but all the anthropometric parameters those have been studied [like body weight (kg), BMI (kg/m2), WC (cm), WHR, WHtR] were significantly higher in urban obese females than their rural counterparts. And we hypothesised such lofty parameters are indicators of different health issues like cardio-vascular diseases, insulin resistance, diabetes mellitus, metabolic syndrome, reproductive hassles, different cancer and so on among both the groups.
Copious studies have been done on obesity prevalence between rural-urban groups in different regions, which remarked that the anthropometric indices were higher in most cases among urban group than rural ones (44,45). Increased body weight and BMI are the yardsticks for generalised obesity and is significantly correlated to different NCDs like asthma, hypertension, dyslipidemia, metabolic syndrome and others as studied in women (46–49). For Indian women WC > 80 cm and WHR > 0.85 is considered as abdominal obesity and significantly associated with cardiovascular problems, diabetes, metabolic syndrome, pulmonary disorders, osteo-arthritis, reproductive problems and so on (50,51).Midha et al. 2014 decided WC > 78cm in women as a cut off for hypertension among Indian (52).WHtR which is now considered a better predictor of NCDs was found high in obese females and associated with different health issues (53–56) including other sever infectious diseases(57,58).
Limitation of the study
The sample size included in the study was not enough to comment on generalised population as we only consider the obese group. The data which have been considered are self-reported so any fabrication can mislead the investigation. Though we predict the possible health risks but due to shortage of resources we could not do biochemical investigation as it may depict explicit picture of the situation studied.