ABSTRACT
Background:
Although studies often report the prevalence of obesity, community-based studies reporting the incidence of overweight or obesity in India are scarce. Such incidence data are crucial for improving projections about the future burden of obesity.
Methods:
A non-concurrent follow-up study was done in 2015 in urban Vellore, Tamil Nadu, among two groups of women aged 30-40 years, with body mass index (BMI) <25 kg/m2 (normal) and BMI ≥25 kg/m2 (overweight/obese) in 2012, to assess changes in BMI. The sampling frame consisted of 473 women: 209 women with BMI <25 kg/m2, and 264 women with BMI ≥25 kg/m2, who were part of a cross-sectional survey in 2012. A randomly selected list of 370 women (80% of the original cohort) was used to trace the women. Measurements at follow-up included weight, height, dietary and other risk factors.
Results:
Of 370 women, 170 (45.9%) were followed up at the end of three years, which included 82 with BMI <25 kg/m2 and 88 with BMI >25 kg/m2. The incidence of overweight (BMI ≥25 kg/m2) in three years, was 29.2% (24/82), among women with a normal BMI (<25 kg/m2) in 2012. Among the 88 women who were overweight/obese in 2012, there was no regression to normal BMI within the three years of follow-up. There was an association between the incidence of overweight and the intake of carbohydrates (adjusted odds ratios (AORs): 3, 95% confidence interval (CI): 1.04 to 8.63) and protein intake (AOR: 20.0, 95% CI:2.5 to 158.3).
Conclusions:
This study found an incidence of nearly one-third (29.2%) of developing high BMI (≥25.0 kg/m2) in 30-40-year-old urban women from Vellore, implying a rapid increase in overweight and obesity among young women.
Keywords: Incidence, obesity, urban, women, young
Introduction
Obesity is one of the most significant but neglected public health problems, leading to increased morbidity and mortality, especially related to non-communicable diseases. The prevalence of overweight and obesity is increasing in Asia, with a higher prevalence among women, making it an important issue for women’s health.[1] The prevalence of obesity among women of reproductive age (15-49 years) in India rose from 23% to 33% between 2005 and 2019.[2] A study done in a slum in north India found obesity in females was 15.6% (95% CI 10.7% to 22.3%) and in males, 13.3% (95% CI 8.5% to 19.5%).[3] A multi-site study found the prevalence of overweight/obesity (body mass index (BMI) >25 kg/m2) was 22.5%, 45.6% and 57.4%, respectively, in rural, urban-poor and urban-middle-class women.[4] The rise in obesity is mainly due to risk transition, with increasing sedentary lifestyles combined with obesogenic diets, exacerbated by increasing urbanisation.
A study among mega cities in India, reported the highest prevalence of overweight or obese urban women in Chennai (39%), compared to other cities.[5] Obesity and cardiovascular risk factors have also been shown to increase with social class.[6]
Analysis of trends % incidence of overweight/obesity over five decades, in women aged 40-55 years in the United States (1950 to 1990), found that the eight-year incidence of overweight was 15.0% in the 1950s, increasing to 33.1% in the 1990s.[7] The 10-year incidence of becoming overweight was 16.5% in men and 13.5% in women aged 35-44 years, in the United States in the 1980s.[8] Although studies often report the prevalence of obesity in India, community-based studies reporting the incidence of overweight or obesity are lacking, particularly among women. As women in India experience their first childbirth at around 21 years,[9] the age group of 30-40 years is a period when many women would be in the post-childbirth phase of life and gain weight, leading to later risk of cardiovascular events.[10] During these years, encounters with general physicians are more likely than those with obstetricians, implying the need for general practitioners to understand the burden of obesity in this group, and supporting women to remain within limits of normal BMI.
This study assessed the three-year incidence of overweight/obesity in women aged 30-40 years with previously normal BMI (<25 kg/m2) and the change in BMI among those who were overweight/obese (BMI ≥25 kg/m2), in Vellore city, Tamil Nadu.
Methodology
A follow-up study was done in 2015 among two groups of women aged 30-40 years in 2012: those with normal BMI <25 kg/m2 in 2012 and those with BMI ≥25 kg/m2 (overweight/obese), to assess changes in BMI (mean change in BMI; incidence of overweight/obesity or decrease towards normal BMI). The sampling frame consisted of women who were part of a cross-sectional study done in 2011-12, to assess cardiovascular risk factors, using the World Health Organization’s (WHO) STEPS methodology. The study was done in one randomly selected street in each of the 48 wards of Vellore city, further details of which have been reported elsewhere.[11] The sampling frame for this follow-up study consisted of 209 women with BMI <25 kg/m2, and 264 with BMI ≥25 kg/m2, who were aged 30-40 years in 2012. A sample size of 169 women with BMI <25 kg/m2 (80% of the original cohort) would give 80% power for estimating an incidence of overweight/obesity of 15%,[8] with an absolute precision of 5.5%. A similar proportion of women with BMI ≥25 kg/m2 was also studied for assessing changes in BMI status. A randomly selected list with 80% of the original survey population was generated (370 out of 473), to be followed up for the present study, with blinding of data collectors regarding initial BMI status [Figure 1].
Figure 1.
Flowchart of women who were followed up
Height and weight were reassessed for the women who participated in follow-up, using a stadiometer and digital weighing scale, after obtaining informed consent. The three readings were taken, and the average was considered to avoid measurement bias. The data collector was unaware of the previous BMI status at the time of reassessment. BMI categories were normal BMI of <25 kg/m2, overweight as a BMI of ≥25 kg/m2, and obese as a BMI of ≥30 kg/m2.[12]
For assessing risk factors for incident obesity/overweight among women with previously normal BMI, previous diet history could not be used, as only fruit and vegetable intake had been recorded in 2012. Therefore, to study risk factors for incident overweight/obesity, prevalence odds ratios were calculated with behavioural risk factor data collected in 2015 (the year of follow-up). Participants were asked about current dietary practices using a 24-h dietary recall, analysed using the database of ‘Nutritive Value of Indian Foods’ developed by the National Institute of Nutrition (NIN).[13] Calorie and fat requirements were calculated, considering physical activity and ideal body weight, according to the Indian Council of Medical Research guidelines.[14] Energy requirements were calculated as 35 kcal/kg/24 h, 41 kcal/kg/24 h and 52 kcal/kg/24 h for sedentary, minimally active and highly active women, respectively, based on ideal body weight. Fat requirements were calculated as 20 g/day, 25 g/day and 30 g/day for sedentary, minimally active and highly active women, respectively, based on ideal body weight. The protein requirement was taken as 0.83 g/kg/day (based on ideal weight), irrespective of physical activity. According to ICMR guidelines, 65%-80% of total energy intake should be contributed by carbohydrates.[14] Total energy from carbohydrates was therefore dichotomised as more than or less than 80% of total dietary energy intake.
The General Health Questionnaire (GHQ-12) was used to assess the presence of a possible mental disorder (positive score: >2).[15] The International Physical Activity Questionnaire (IPAQ) was used for physical activity measurement, with classification as minimally active, health-enhancing physical activity (HEPA) and inactive.[16] The minimum pattern of activity to be classified as minimally active was any one of the following criteria: a) three or more days of vigorous activity of at least 20 min per day or b) five or more days of moderate-intensity activity or walking of at least 30 min per day or c) five or more days of any combination of walking, moderate-intensity or vigorous intensity activities, achieving a minimum of at least 600 metabolic equivalent task (MET)-min/week. The two criteria for classification as HEPA were: a) vigorous-intensity activity on at least three days, achieving a minimum of at least 1500 MET-min/week or b) seven or more days of any combination of walking, moderate-intensity or vigorous-intensity activities achieving a minimum of at least 3000 MET-min/week. Those individuals who did not meet the criteria for either of the previously mentioned were considered inactive.[16,17] Socioeconomic status was measured using the modified Kuppuswamy scale 2015.[18]
The study was approved by the Ethics Committee and Institutional Review Board of the institution (IRB Min No 9237, dated 12-01-2015). Data entry was done using Epidata 3.1 (Odense, Denmark), and statistical analysis was done with SPSS version 24.0 (Chicago, Illinois). Mean and standard deviation (SD) or median with interquartile range (IQR) were used for descriptive statistics of continuous variables, frequencies computed for categorical variables and incidence calculated with 95% confidence interval (CI). Student’s t-test was used to compare means, Chi-square test was used for categorical variables and binary logistic regression was used to obtain adjusted odds ratios (AORs), with P < 0.05 considered as significant.
Patient and Public involvement: No patient involved and no public involvement.
Results
Of 209 women who were surveyed in 2012 with normal weight (BMI <25 kg/m2), the randomly selected blinded sampling frame (without initial BMI status mentioned) included 169 normal-weight women (80% of the original cohort). Of these 169, 82 (48.5%) women were successfully followed up at the end of three years, one was unwilling to participate, one was excluded due to pregnancy, 28 had moved away (16.6% migration) and 57 (33.7%) were not available at their homes even after two visits. Of the 264 women with BMI ≥25 kg/m2 in 2012, the blinded sampling frame had 201 women (75% of the original cohort), of which 88 (43.8%) were successfully followed up in 2015. Reasons for failure to follow-up were pregnancy (n = 2), refusal (n = 3), migration (38, 18.9%) and unavailability at home despite two home visits (70, 26.0%), Figure 1.
Sociodemographic characteristics of the women who were followed up are shown in Table 1. The mean age at baseline (2011-12) was 34.3 years (SD: 2.8 years), while the literacy rate was 67.1%. The majority of the women (61%) belonged to the upper-lower socioeconomic group, according to the modified Kuppusamy scale 2015.
Table 1.
Baseline characteristics of the two cohorts of women who were followed up
| Variables | Categories | Normal BMI group (Baseline BMI <25 kg/m2) N out of 82 (%) | Overweight/obese group (Baseline BMI ≥25 kg/m2) N out of 88 (%) |
|---|---|---|---|
| Age | 30–35 years | 30 (37%) | 55 (62.5%) |
| 36–40 years | 52 (63%) | 33 (37.5%) | |
| Marital status | Married | 70 (85.4%) | 81 (92%) |
| Single | 7 (8.5%) | 2 (2.3%) | |
| Widowed/separated/divorced | 5 (6.1%) | 5 (5.6%) | |
| Occupation | Housewife | 67 (81.7%) | 71 (80.7%) |
| Unskilled labour | 12 (14.6%) | 9 (10.2%) | |
| Semiskilled/skilled labour | 2 (2.4%) | 5 (5.7%) | |
| Semiprofessional | 1 (1.2%) | 3 (3.4%) | |
| Education in years | Nil | 14 (17.1%) | 9 (10.2%) |
| 1-4 | 4 (4.9%) | 4 (4.5%) | |
| 5-8 | 15 (18.3%) | 35 (39.8%) | |
| 9-10 | 37 (45.1%) | 22 (25%) | |
| >10 | 12 (14.7%) | 18 (20.4%) | |
| Social class (Modified Kuppusamy 2015) | Upper/Upper Middle | 9 (11%) | 19 (21.6%) |
| Lower Middle | 21 (25.6%) | 24 (27.3%) | |
| Upper Lower/Lower | 52 (63.4%) | 45 (51.1%) |
The incidence of becoming overweight (BMI ≥25 kg/m2) in three years, was 29.3% (24/82, 95% CI: 19.25%–39.35%) in this sample of urban women aged 30-40 years with normal baseline BMI (<25 kg/m2). However, there was no development of obesity (BMI ≥30 kg/m2) at the three years follow-up assessment, among this group.
Among the women who were already overweight/obese in 2012, there was no regression to normal BMI within the three years of follow-up. All these 88 women continued to have a BMI ≥25 kg/m2, with 27.7% of initially overweight (BMI: 25-29 kg/m2) women becoming obese in three years (BMI ≥30 kg/m2). Table 2 demonstrates changes in BMI status at the end of three years, according to previous BMI. The median three-year gain in BMI in the group with normal BMI at baseline, was +1.55 kg/m2 (IQR: +0.84 to +2.32 kg/m2), while it was +1.39 kg/m2 (IQR: +0.74 to +2.6 kg/m2) in the group which was overweight at baseline and +0.83 kg/m2 (IQR: +0.24 to +2.84 kg/m2) in those who were obese at baseline, P value for test of medians 0.067.
Table 2.
Changes in BMI among urban women aged 30-40 years from 2012 to 2015
| Previous BMI status | Total | Current BMI <25.0 kg/m2 | Current BMI 25.0-29.9 kg/m2 | Current BMI ≥30.0 kg/m2 |
|---|---|---|---|---|
| Normal (<25.0 kg/m2) | 82 | 58 (70.3%) | 24 (29.3%) | 0 (0%) |
| Overweight (25.0–29.9 kg/m2) | 65 | 0 (0%) | 47 (72.3%) | 18 (27.7%) |
| Obese (≥30.0 kg/m2) | 23 | 0 (0%) | 1 (4.3%) | 22 (95.7%) |
The sociodemographic and other lifestyle factors associated with incident overweight/obesity in women with initial normal BMI are shown in Table 3, along with AORs. A higher proportion of women who had become overweight (BMI ≥25 kg/m2) reported consuming a carbohydrate-dense diet, compared to women whose BMI had remained normal after three years (75% vs 50%, Chi-square P value 0.03, unadjusted odds ratio: 3.00, 95% CI: 1.04 to 8.63), although there was no significant association after adjusting for confounding factors, Table 3. Those who became overweight/obese in three years were more likely to have been older at baseline (75.0%) than those who remained normal (58.6%), although this was not statistically significant, AOR: 1.71 (95% CI: 0.46 to 6.37).
Table 3.
Factors affecting the incidence of overweight/obesity in women with normal BMI at baseline
| Factors | Categories | Became overweight/obese in 3 years (BMI ≥25 kg/m2) n=24 | Remained normal weight in 3 years (BMI <25 kg/m2) n=58 | Adjusted odds ratio with 95% confidence interval, P |
|---|---|---|---|---|
| Age in years at baseline | ≥36 | 18 (75%) | 34 (58.6%) | 1.71 (0.46 to 6.37), 0.42 |
| <36 | 6 (25%) | 24 (41.3%) | ||
| Education in years | <8th standard | 7 (29.1%) | 26 (44.8%) | 2.59 (0.74 to 9.04), 0.13 |
| ≥8th standard | 17 (70.8%) | 32 (55.1%) | ||
| Social class | Upper/middle | 11 (45.8%) | 19 (32.7%) | 1.26 (0.38 to 4.21), 0.71 |
| Lower | 13 (54.1%) | 39 (67.2%) | ||
| Current physical activity (IPAQ) | Inactive | 7 (29.1%) | 20 (34.5%) | 0.72 (0.19 to 2.65) 0.63 |
| Active | 17 (70.8%) | 38 (65.5%) | ||
| Common mental disorders screening (GHQ score) | Yes (≥3) | 9 (37.5%) | 18 (31.1%) | 1.09 (0.34 to 3.56) 0.88 |
| No (<3) | 15 (62.5%) | 40 (68.9%) | ||
| Current total calorie intake per day based on the activity | >required | 17 (70.8%) | 29 (50%) | 1.14 (0.14 to 9.69) 0.90 |
| ≤required | 7 (29.1%) | 29 (50%) | ||
| Current total energy intake from carbohydrates | >80% | 18 (75%) | 29 (50%) | 1.93 (0.57 to 6.52) 0.29 |
| ≤80% | 6 (25%) | 29 (50%) | ||
| Current protein intake per day | >0.83 g/kg | 23 (95.8%) | 31 (53.4%) | *14.39 (1.74 to 119.35) 0.01 |
| ≤0.83 g/kg | 1 (4.1%) | 27 (46.5%) | ||
| Current fat intake per day based on activity | >required | 6 (25%) | 17 (29.3%) | 1.03 (0.23 to 4.63) 0.97 |
| ≤required | 18 (75%) | 41 (70.6%) | ||
| Duration of sleep at night | <8 h | 13 (54.1%) | 27 (46.55%) | 0.64 (0.09 to 4.17) 0.64 |
| ≥8 h | 11 (45.83%) | 31 (53.45%) |
*P<0.05
The majority of the women (95.8%) who became overweight/obese (BMI ≥25 kg/m2) reported an intake of protein per day of >0.83 g/kg, compared to 53.4% of those whose BMI remained below 25 kg/m2 (adjusted OR: *14.39, 95% CI 1.74 to 119.35).
Mean values of current daily calories, carbohydrates, proteins and fats were also compared between women who had become overweight/obese in three years and those who had not. Women with new onset overweight/obesity (BMI ≥25 kg/m2) reported a current mean ± SD calorie intake of 1608.96 ± 347.47 kcal, compared to 1439.8 ± 344.60 kcal for those who remained normal (BMI <25 kg/m2), t statistic: 2.018, P value 0.047. There were no significant differences in mean carbohydrate, protein and fat intake, respectively, among women who became overweight/obese, compared to those who did not (carbohydrates: 283.24 g ± 55.09 g vs 261.26 g ± 66.09 g, t-test P value 0.155; proteins: 43.42 g ± 12.50 g vs 38.95 ± 14.35 g, t-test P value 0.187; fats: 29.69 g ± 12.23 g vs 27.14 g ± 14.36 g, t-test P value 0.448).
Discussion
The three-year cumulative incidence of becoming overweight (BMI ≥25 kg/m2, considered obese by Asia Pacific standards),[19] among urban women from Vellore city was 29.2%, indicating the rapid increase in the burden of obesity. Although these findings are not generalisable to all urban areas in India, these results from a tier 2 city were much higher than the 10-year incidence of obesity in women aged 35-44 years of 13.5% in the United States in the 1980s.[8] The prevalence of obesity in urban women aged 15-49 years in Tamil Nadu was 46.1%, as compared to 35.4% in rural women (National Family Health Survey, NFHS-5, 2019-2021), increasing from 36.2% and 25.4%, respectively, in 2015-2016.[20]
The increase in BMI with age has been shown in multiple studies. Population-based cohort studies from Australia found that the rate of weight gain in 4 years was greater in women born between 1989 and 1995 compared to those born in 1873-78, indicating that the rate of weight gain is a greater problem now than before.[21]
It was also of concern, that none of the overweight women reverted to a normal BMI in 3 years in our study, and one in four overweight women became obese, showing inadequate lifestyle modifications followed by these young urban women. Lack of weight loss in overweight women may be either due to ignorance of the need for weight loss or due to failed attempts, which were not measured. Another cohort study from West Bengal found that the 9-year incidence of overweight (BMI ≥23 kg/m2) was 27.2% among adult women, while our study showed a similar rate in three years, using a higher BMI cut-off of 25 kg/m2.[22] This finding confirms the higher burden of obesity in southern India, as a national survey in 2017-18 also showed that the prevalence of overweight (BMI ≥25 kg/m2) was 44.7% among women in south India, compared to 28.1% in women from eastern India.[23]
A study in the United States showed that the rate of weight gain was more important than baseline weight, in influencing cardiovascular risk in young adults who maintained their weight over 15 years, for both normal weight and overweight women.[24] Thus, it is important to halt weight gain, even if weight loss is very difficult to achieve.
While young women are known to be at high risk of weight gain, there is not enough evidence for the causes of this.[25] In our study from urban Vellore, socioeconomic status (measured using a modified Kuppuswamy scale) was not significantly associated with becoming overweight/obese in 3 years, while the cohort study from West Bengal and a previous study from Vellore has shown that the prevalence of obesity was higher in higher social classes.[6,22] This may be due to the limitation of our study to only young women, lower numbers of women in the highest socioeconomic groups and a short 3-year time frame. The West Bengal study found that female sex, younger age groups (<36 years) and higher socioeconomic status were risk factors for incident overweight.
A detailed diet history was not part of the WHO STEPS survey, so caloric and nutrient intake at baseline was not available in this study, and hence our findings of dietary habits with incident overweight/obesity are measures of association and hence can be biased by reverse causation. We found that those whose protein intake was more than or equal to the recommended dietary allowance (RDA) were 14 times more likely to have developed overweight/obesity, compared to those with inadequate protein intake, after adjusting for social class and other factors. This was in contrast to a study in the United States which showed that 20% higher protein intake resulted in a 50% lower body weight regain.[26] However, in India, protein intake is more likely to be plant protein, rather than animal protein, predominantly (60%) from cereals,[27] which could also explain the association with weight gain. In India, those who have lower protein intake are more likely to also have low-calorie intake and hence lower weight gain.[28] Although most Indians currently have a diet low in proteins and calories, with an increase in excess consumption of proteins and calories, weight gain is inevitable, especially because it is often accompanied by physical inactivity and higher fat intake.
The NIN recommends a wide range of percent of energy from carbohydrates 55%-75%.[14] In this study, those whose consumption of carbohydrates was more than 80% of total energy intake were more likely to become overweight in 3 years. A systematic review done by Sartorius et al.[29] found that it cannot be concluded that a high-carbohydrate diet or increased percentage of total energy intake in the form of carbohydrates increases the odds of obesity, but the review was limited by wide heterogeneity in studies and lack of standardised measures in studies.
Self-reporting of dietary intake was the only form of dietary assessment, which is a limitation of the study, which implies that there could be under-reporting or over-reporting of various food components. Another limitation was the loss of follow-up of participants, which is a common problem in urban areas, as people change addresses due to work reasons and are also difficult to contact due to busy schedules.
The alarming increase in obesity in young women needs urgent steps for primary prevention using a life course approach, focussing on children, adolescents, young adults, periconceptional, antenatal and post-natal women and their families, to decrease the morbidity and mortality associated with obesity. Given that pregnancy and the post-partum period contribute to weight gain,[9] primary care physicians and obstetricians have an important role in managing weight gain, as well as supporting the maintenance of healthy BMI during pre-conception, antenatal and post-natal periods. Interventions need to include both primary prevention of obesity through healthy lifestyles, as well as screening for unhealthy pre-pregnancy BMI, with an increase in government action to tackle the obesity epidemic.[30]
Women in India are expected to fulfil multiple responsibilities at home and at work (if employed) and find it difficult to take care of their own health. It is important for the development of the economy and maintenance of a healthy population, to enable women with knowledge, supportive environments and healthcare inputs, to avoid problems related to obesity and related morbidity. Creating healthy settings at work and communities, including outdoor gyms, safe walking spaces and indoor gyms in offices, are all part of possible activities that could be taken up and maintained by local administrations.
Ethical clearance
The study was approved by Institutional Ethics Committee Christian Medical College (approval 9237 IRB minutes dated on 12/1/2015).
Key message
What is already known on this topic
Many studies have reported the trends in the prevalence of obesity in India, with higher rates among women, but studies reporting the incidence of overweight or obesity, are lacking, particularly among women who are in the reproductive age group.
What this study adds
Almost a third (29.3%) of urban women aged 30-40 years with a normal baseline body mass index (BMI) (<25 kg/m2) became overweight in three years in this cohort of women from Vellore, Tamil Nadu, south India. The median gain in BMI within three years was 1.55 kg/m2.
How this study might affect research, practice or policy
The alarming increase in obesity in young women needs urgent steps by primary care physicians for primary and secondary prevention using a life course approach, focussing on childhood, adolescence and young adulthood, to decrease the morbidity and mortality associated with obesity-related diseases.
Financial support and sponsorship
Christian Medical College Vellore, Internal Fluid Research grant 9237.
The original baseline survey in 2012 was funded by the Indian Council of Medical Research no. 50/3/TF/DV/06-NCD-II.
Conflicts of interest
There are no conflicts of interest.
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