ABSTRACT:

Objective:

To investigate the role of the domiciliary situation in the prevalence of general and abdominal obesity through the National Health Survey of 2013.

Methodology:

General obesity (body mass index ≥ 30 kg/m²) and abdominal obesity (waist circumference ≥ 102 cm in men and ≥ 88 cm in women) in rural and urban areas were described according to sex and macroregion. Crude and adjusted Poisson regression models were used to test the association between obesity and household situation, with the significance level of 5%.

Results:

The study included 59,226 individuals. Out of these, 20.7% presented general obesity and 38% abdominal obesity (higher in women: 24.3 and 52%, respectively). The highest prevalences of general obesity were observed in southern urban areas, for both sexes (20.8% in men and 26.5% in women). In rural areas, the highest prevalences were observed for the central-west region (17.2%) in men and in the south region (27.4%) in women. In males, after adjusting for demographic variables, living in rural areas was associated with lower prevalences of general obesity in the North (prevalence ratios - PR = 0.60; confidence interval of 95% - 95%CI 0.40 - 0.89) and Northeast (PR = 0.47, 95%CI 0,38 - 0.59), and for abdominal obesity in all regions. For women in the Midwest, the rural household situation was associated with lower prevalences of obesity. (PR = 1.11, 95%CI 1.01 - 1.23).

Conclusions:

The results evidenced the role of the domiciliary situation among outcomes at the national level, with lower prevalence of general and abdominal obesity in men living in rural areas. However, higher prevalences were found among women, especially for abdominal obesity.

Keywords:
Obesity; Abdominal Obesity; Health Surveys; Public health

INTRODUCTION

General obesity is considered a risk factor for individual health, leading to cerebrovascular accident, hypertension, dyslipidemias, diabetes mellitus and certain types of cancer¹1. World Health Organization. Obesity: preventing and managing the global epidemic. Report of a World Health Organization Consultation. Obesity Technical Report Series no. 284. Genebra: World Health Organization; 2000. 256 p.. The assessment of abdominal fat, compared to other anthropometric indicators, is one of the best predictors of visceral fat, which is strongly correlated with most metabolic risk factors²2. Vasques ACJ, Priore SE, Rosado LEFPL, Franceschini SCC. Utilização de medidas antropométricas para a avaliação do acúmulo de gordura visceral. Rev Nutr 2010; 23(1): 107-18. http://dx.doi.org/10.1590/S1415-52732010000100012
http://dx.doi.org/10.1590/S1415-52732010... and considered an independent risk factor for cardiovascular diseases³3. Pinho CP, Diniz A da S, Arruda IK, Batista Filho M, Coelho PC, Sequeira LA, et al. Prevalência e fatores associados à obesidade abdominal em indivíduos na faixa etaria de 25 a 59 anos do Estado de Pernambuco, Brasil. Cad Saúde Pública 2013; 29(2): 313-24. http://dx.doi.org/10.1590/S0102-311X2013000200018
http://dx.doi.org/10.1590/S0102-311X2013... .

Rural populations have low schooling, low income, poor access to health services and more frequent risk factors, such as hypertension and diabetes mellitus⁴4. Dias EC. Condições de vida, trabalho, saúde e doença dos trabalhadores rurais no Brasil. In: Pinheiro TMM, org. Saúde do trabalhador rural - RENAST. Brasília: Ministério da Saúde; 2006. p. 1-27.^,55. Witeck G, Franz L, Busnello M, Battisti I, Marchi D, Berlezi E, et al. Índices antropométricos e fatores de risco cardiovasculares entre mulheres residentes em uma área rural do estado do Rio Grande do Sul. Sci Med 2010; 20(4): 282-8.. Rural areas differ from urban areas in terms of demographic, socioeconomic and cultural characteristics, factors that are known to be important in determining overweight at the population level⁶6. Neuman M, Kawachi I, Gortmaker S, Subramanian SV. Urban-rural differences in BMI in low- and middle-income countries: the role of socioeconomic status. Am J Clin Nutr 2013; 97(2): 428-36. https://doi.org/10.3945/ajcn.112.045997
https://doi.org/10.3945/ajcn.112.045997... ^,77. Neuman M, Kawachi I, Gortmaker S, Subramanian S. National economic development and disparities in body mass index: a cross-sectional study of data from 38 countries. PloS One 2014; 9(6): e99327. https://doi.org/10.1371/journal.pone.0099327
https://doi.org/10.1371/journal.pone.009... . Although still difficult to measure, urbanization and better access to mechanization have been suggested as important factors in increasing the prevalence of obesity in rural areas around the world⁶6. Neuman M, Kawachi I, Gortmaker S, Subramanian SV. Urban-rural differences in BMI in low- and middle-income countries: the role of socioeconomic status. Am J Clin Nutr 2013; 97(2): 428-36. https://doi.org/10.3945/ajcn.112.045997
https://doi.org/10.3945/ajcn.112.045997... . The impact of such factors can be observed through results of changes in eating habits, behaviors and lifestyle⁸8. Monda KL, Gordon-Larsen P, Stevens J, Popkin BM. China’s transition: the effect of rapid urbanization on adult occupational physical activity. Soc Sci Med 2007; 64(4): 858-70. https://doi.org/10.1016/j.socscimed.2006.10.019
https://doi.org/10.1016/j.socscimed.2006... ^,99. Assah FK, Ekelund U, Brage S, Mbanya JC, Wareham NJ. Urbanization, physical activity, and metabolic health in sub-Saharan Africa. Diabetes Care 2011; 34(2): 491-6. https://doi.org/10.2337/dc10-0990
https://doi.org/10.2337/dc10-0990... ^,1010. Silva KS, Lopes AS, Silva FM. Comportamentos sedentários associados ao excesso de peso corporal. Rev Bras Educ Fís Esporte 2007; 21(2): 135-41. https://doi.org/10.1590/S1807-55092007000200005
https://doi.org/10.1590/S1807-5509200700... ^,1111. Malik VS, Willett WC, Hu FB. Global obesity: trends, risk factors and policy implications. Nat Rev Endocrinol 2013; 9(1): 13-27. https://doi.org/10.1038/nrendo.2012.199
https://doi.org/10.1038/nrendo.2012.199... .

Few studies have sought to evaluate the role of household situation in determining these outcomes in Brazil and in the world. Studies have reported differences in the prevalence of obesity according to household situations. Higher values have been reported among urban residents in middle- and low-income countries, while comparable values between both situations are observed in high-income countries⁶6. Neuman M, Kawachi I, Gortmaker S, Subramanian SV. Urban-rural differences in BMI in low- and middle-income countries: the role of socioeconomic status. Am J Clin Nutr 2013; 97(2): 428-36. https://doi.org/10.3945/ajcn.112.045997
https://doi.org/10.3945/ajcn.112.045997... ^,77. Neuman M, Kawachi I, Gortmaker S, Subramanian S. National economic development and disparities in body mass index: a cross-sectional study of data from 38 countries. PloS One 2014; 9(6): e99327. https://doi.org/10.1371/journal.pone.0099327
https://doi.org/10.1371/journal.pone.009... ^,1212. Batista Filho M, Rissin A. A transição nutricional no Brasil: tendências regionais e temporais. Cad Saúde Pública 2003; 19(Supl. 1): S181-91. http://dx.doi.org/10.1590/S0102-311X2003000700019
http://dx.doi.org/10.1590/S0102-311X2003... ^,1313. Freedman DM, Ron E, Ballard-Barbash R, Doody MM, Linet MS. Body mass index and all-cause mortality in a nationwide US cohort. Int J Obes 2006; 30(5): 822-9. https://doi.org/10.1038/sj.ijo.0803193
https://doi.org/10.1038/sj.ijo.0803193... ^,1414. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004; 363(9403): 157-63. https://doi.org/10.1016/S0140-6736(03)15268-3
https://doi.org/10.1016/S0140-6736(03)15... .

According to the latest census by the Brazilian Institute of Geography and Statistics (IBGE), about 30 million people live in rural areas of Brazil, corresponding to 15.6% of the national population, with the highest proportions in the North and Northeast regions¹⁵15. Instituto Brasileiro de Geografia e Estatística. Censo demográfico 2010: Características da população e dos domicílios. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2010.. As in other countries, obesity in Brazil is considered an epidemics¹⁶16. Pinheiro ARO, Freitas SFT, Corso ACT. Uma abordagem epidemiológica da obesidade. Rev Nutr 2004; 17(4): 523-33. http://dx.doi.org/10.1590/S1415-52732004000400012
http://dx.doi.org/10.1590/S1415-52732004... . Although there is a worldwide consensus about the importance of studying the prevalence of obesity in rural areas, few studies of national representativity are reported in Brazil.

The present study aims to investigate the role of household situation across Brazilian macroregions in the prevalence of general and abdominal obesity using the largest population survey conducted in the country in 2013.

METHODOLOGY

This is a descriptive, cross-sectional, population-based study conducted in 2013 in the national territory, consisting of the census tracts of the Geographic Operational Base from the Demographic Census 2010¹⁵15. Instituto Brasileiro de Geografia e Estatística. Censo demográfico 2010: Características da população e dos domicílios. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2010., excluding areas with special characteristics and reduced population. The National Health Survey (“Pesquisa Nacional de Saúde”, PNS)¹⁷17. Instituto Brasileiro de Geografia e Estatística. Pesquisa Nacional de Saúde 2013: percepção do estado de saúde, estilos de vida e doenças crônicas. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística ; 2014. is part of the IBGE’s Integrated Household Survey System and functions on the basis of its master sample, with greater geographic coverage and precision gain for specific health estimates.

Conglomerate sampling was used in three stages. Since primary sampling units are considered as census tracts and households are second-stage units, residents aged 18 years or more defined the third-stage units. Therefore, only one individual per household was selected through a simple random process and invited to participate in the research. Weights were applied based on the probability of sample participation, thus guaranteeing accurate representativeness of Brazil, macroregions and household situation. Further details can be found in PNS technical reports¹⁷17. Instituto Brasileiro de Geografia e Estatística. Pesquisa Nacional de Saúde 2013: percepção do estado de saúde, estilos de vida e doenças crônicas. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística ; 2014.^,1818. Instituto Brasileiro de Geografia e Estatística. Pesquisa Nacional de Saúde, 2013. Antropometria e pressão arterial. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística ; 2016..

We assessed weight, height and waist circumference (WC) of individuals aged 18 years or older, of both genders. Women who reported being or suspected of being pregnant at the time of the interview were excluded from the analyzes. Nutritional status was defined by body mass index (BMI), by dividing weight (in kilograms) by height (in meters) squared, and classified as eutrophic (BMI up to 24.9 kg/m²), overweight (BMI from 25 to 29.9 kg/m²) and obesity (BMI ≥ 30 kg/m²). The cutoff point for obesity was considered to define the outcome in the analysis (yes or no). Regarding abdominal obesity, WC was used, corresponding to the substantially increased risk or level II (WCII) (WCII ≥ 102 cm for men and ≥ 88 cm for women)¹⁹19. World Health Organization. Expert Committee. Physical Status: the use and interpretation of anthropometry. Technical Report Series, 854. Genebra: World Health Organization ; 1995.. This information was assessed and classified according to the recommendations of the World Health Organization (WHO)¹⁹19. World Health Organization. Expert Committee. Physical Status: the use and interpretation of anthropometry. Technical Report Series, 854. Genebra: World Health Organization ; 1995..

To gather anthropometric variables, PNS had two measurements of height, WC and weight, and considered the average when values were equal or differed, at most in 1 cm for height and WC or 0.5 kg for weight, at most¹⁸18. Instituto Brasileiro de Geografia e Estatística. Pesquisa Nacional de Saúde, 2013. Antropometria e pressão arterial. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística ; 2016.. In cases where only one of the measures was informed, this value was adopted as final value of the analysis variable. For weight and/or height, total data imputation was 12.7% for men and 12.5% for women. For WC, the imputation percentage was around 8% (8.01 and 8.07% for men and women, respectively)¹⁸18. Instituto Brasileiro de Geografia e Estatística. Pesquisa Nacional de Saúde, 2013. Antropometria e pressão arterial. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística ; 2016..

Outcomes were described and stratified by gender. The analyzes aiming at testing the association between household situation and the outcomes were stratified by gender and macroregions.

Data was processed in the Stata 14.0 software (StataCorp, College Station, Texas, USA), and the cluster sampling effect was considered in all analyzes by the “survey” command. Prevalences in each region were compared by the χ² test for heterogeneity. The difference in prevalence of general and abdominal obesity between genders in each household situation was calculated based on a decrease in the prevalence of general and abdominal obesity in women compared to respective values in men living in urban and rural areas, according to macroregions. To compare household situations, we performed crude and adjusted Poisson regression, with two adjustment models.

The first model included the variables age (18 to 24, 25 to 34, 35 to 44, 45 to 54, 55 to 64, and 65 years or more) and skin color (white, black, yellow, brown or indigenous) The second model included the variables age, skin color, marital status (measured by the question “Do you live with a spouse or partner?” and answers “no” or “yes”), schooling (no education or incomplete elementary; complete primary or incomplete high school; complete high school or incomplete higher education; complete higher education), and index of assets (in quintiles).

Because they were considered potential mediators of the association with household situation, the outcomes for schooling, income and marital status were added to the second model. The value of p=0.05 defined factors associated with the outcome.

The study was approved by the Research Ethics Committee of the Medical School of Universidade Federal de Pelotas [Federal University of Pelotas], under opinion number 2,423,849.

RESULTS

The sample of interest in our study was of 59,226 individuals. Of these, 52.9% were females, 21.7% were between 25 and 34 years old, 47.4% had white skin color, 38.2% had complete high school or incomplete higher education, 61.5% were married, and 23.6% belonged to the richest income quintile. As for macroregion, 44.0% lived in the Southeast. Of the total sample, 86.2% were urban dwellers. The prevalence of overweight was 36.1% (38.7% for men and 33.7% for women, p<0.001). The prevalence of general obesity was 20.8% (16.8% in males and 24.3% in females, p<0.001) and abdominal obesity was 38% (22.3% in males and 52.0% in females, p<0.001) (Table 1).

A clear heterogeneity of the outcomes evaluated between macroregions is seen (Table 2). Considering general obesity in the urban area, prevalence was 17.8% in males and 24.7% in females, with the highest prevalences in the Southern Region for both genders (20.8% in males and 26.5% in females) (Table 2). In rural areas, prevalences were 11.0% in males and 21.8% in females. The highest prevalences were found in the Midwest among males (17.2%) and in the Southern among women (27.4%) (Figure 1). As for abdominal obesity in urban areas, prevalences were 23.7% in men and 52.1% in women. Higher prevalences in the urban area were found in the South among males (29.1%) and in the Southeast among females (57.4%). In rural areas, prevalences were 14.8% for males and 51.5% for females. Higher prevalences were found in the South for men (22.3%) and in the Southeast for women (57.4%) (Figure 2).

Comparing prevalences according to gender, higher rates of obesity were found among women, with differences between men and women in rural areas, both for general obesity (10.8 percentage points - pp) and for abdominal obesity (36.7 pp). Values of difference reached 14.6 pp of prevalence of general obesity in rural regions in the Southeast and 40.1 pp of prevalence of abdominal obesity in rural areas in the Northeast (Table 2).

In order to test the effect of household situation on the prevalence of obesity in the national territory and in each macroregion, the Poisson regression was used. In the crude analysis, lower prevalences of general obesity were observed in rural areas for the North and Northeast regions among men. Considering abdominal obesity, lower prevalences were found in rural areas of all regions, except in the South. When adjusted for age and skin color, associations with general obesity in the North and Northeast regions remained significant (prevalence ratio -PR = 0.60, 95% confidence interval - 95%CI 0.40 - 0.89 and PR = 0.47, 95%CI 0.38 - 0.59, respectively). For abdominal obesity, all regions had a statistically significant association, even in the South (PR = 0.75, 95%CI 0.61 - 0.93). After inclusion of the variables schooling, marital status and income, the associations in the Northeast Region taking into account general obesity (PR = 0.64, 95%CI 0.50 - 0.81) and abdominal obesity (PR = 0.64, 95%CI 0.51 - 0.74) were maintained (Table 3).

As for women, prevalences of general and abdominal obesity in rural and urban areas were similar, except in the Midwest Region, the rural area being associated with a higher prevalence of abdominal obesity after adjusting for age and skin color (PR = 1.11, 95%CI 1.01-1.23). After including the variables schooling, marital status and income, association with abdominal obesity was observed only in the Northeast Region (PR = 0.88, 95%CI 0.81-0.96) (Table 3).

DISCUSSION

In this study, the severity of the general and abdominal obesity epidemics in rural and urban areas of Brazil is disclosed by the values originating from data of national representativity. We identified an important effect of household situation on outcomes at the national level, with a notable difference between genders.

The national prevalence of general obesity found in this study was higher than observed in the Household Budget Survey²⁰20. Instituto Brasileiro de Geografia e Estatística. Pesquisa de orçamentos familiares 2008-2009: antropometria e estado nutricional de crianças, adolescentes e adultos no Brasil. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística ; 2010. in 2008-2009. In this survey, prevalences in urban areas reached 13.2% for men and 17.0% for women, while prevalences in rural areas reached 8.8% and 16.5%, respectively, for men and women. Moreover, the prevalence of general obesity described in this study for the rural area is in agreement with the few studies carried out in rural areas of Brazil (varying from 5.5% in Minas Gerais²¹21. Mendes LL, Gazzinelli A, Velasquez-Melendez G. Fatores associados à resistência à insulina em populações rurais. Arq Bras Endocrinol Metabol 2009; 53(3): 332-9. http://dx.doi.org/10.1590/S0004-27302009000300006
http://dx.doi.org/10.1590/S0004-27302009... to 29.5% in Rio Grande do Sul²²22. Martins-Silva T, Loret de Mola C, Vaz JS, Tovo-Rodrigues L. Obesidade geral e abdominal em adultos residentes em zona rural no Sul do Brasil. Rev Saúde Pública 2018; 52(Supl. 1): 3s. http://dx.doi.org/10.11606/s1518-8787.2018052000264
http://dx.doi.org/10.11606/s1518-8787.20... ), in the United States (39.6 to 45.7%)²³23. Hodge FS, Cantrell BG, Kim S. Health status and sociodemographic characteristics of the morbidly obese American Indians. Ethnicity Dis 2011; 21(1): 52-7.^,2424. Befort CA, Nazir N, Perri MG. Prevalence of obesity among adults from rural and urban areas of the United States: findings from NHANES (2005-2008). J Rural Health 2012; 28(4): 392-7. https://doi.org/10.1111/j.1748-0361.2012.00411.x
https://doi.org/10.1111/j.1748-0361.2012... , Turkey (30.3%)²⁵25. Oguz A, Temizhan A, Abaci A, Kozan O, Erol C, Ongen Z, et al. Obesity and abdominal obesity; an alarming challenge for cardio-metabolic risk in Turkish adults. Anadolu Kardiyol Derg 2008; 8(6): 401-6., South-Eastern Limestone Coast region in Australia (30.0%)²⁶26. Janus ED, Laatikainen T, Dunbar JA, Kilkkinen A, Bunker SJ, Philpot B, et al. Overweight, obesity and metabolic syndrome in rural southeastern Australia. Med J Australia 2007; 187(3): 147-52. https://doi.org/10.5694/j.1326-5377.2007.tb01171.x
https://doi.org/10.5694/j.1326-5377.2007... , and South Africa (27.2%)²⁷27. Sartorius B, Veerman LJ, Manyema M, Chola L, Hofman K. Determinants of Obesity and Associated Population Attributability, South Africa: Empirical Evidence from a National Panel Survey, 2008-2012. PloS One 2015; 10(6): e0130218. https://doi.org/10.1371/journal.pone.0130218
https://doi.org/10.1371/journal.pone.013... .

When stratified by region, the results resemble those of the Household Budget Survey in 2008-2009²⁰20. Instituto Brasileiro de Geografia e Estatística. Pesquisa de orçamentos familiares 2008-2009: antropometria e estado nutricional de crianças, adolescentes e adultos no Brasil. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística ; 2010., which reported higher prevalences of general obesity in the urban area of the South Region in men (16.4%) and women (19.3%). In the same survey, the rural area of the South Region was also reported as holding the highest prevalence of obesity in men (13.8%) and women (21.2%). Using data from PNS 2012-2013, the South also appeared as the region with the highest prevalence among women living in rural areas and showed one of the highest values among men, however higher than those reported by the first survey. The differences found between both studies may be due to factors such as time elapsed between surveys, differences in sampling methods and anthropometric data collection.

Regarding abdominal obesity, the lack of large surveys in rural areas restricts the possibility of comparisons. However, the findings of this study are in agreement with the high prevalences reported in specific studies for Brazilian rural areas, varying from 11.6% in the Southeast Region (Minas Gerais)²⁸28. Pimenta AM, Gazzinelli A, Velasquez-Melendez G. Prevalência da síndrome metabólica e seus fatores associados em área rural de Minas Gerais (MG, Brasil). Ciênc Saúde Coletiva 2011; 16(7): 3297-306. http://dx.doi.org/10.1590/S1413-81232011000800029
http://dx.doi.org/10.1590/S1413-81232011... to 37.8% in the South Region (Pelotas)²²22. Martins-Silva T, Loret de Mola C, Vaz JS, Tovo-Rodrigues L. Obesidade geral e abdominal em adultos residentes em zona rural no Sul do Brasil. Rev Saúde Pública 2018; 52(Supl. 1): 3s. http://dx.doi.org/10.11606/s1518-8787.2018052000264
http://dx.doi.org/10.11606/s1518-8787.20... . A study conducted with women in the South Region of the country (Catuípe)⁵5. Witeck G, Franz L, Busnello M, Battisti I, Marchi D, Berlezi E, et al. Índices antropométricos e fatores de risco cardiovasculares entre mulheres residentes em uma área rural do estado do Rio Grande do Sul. Sci Med 2010; 20(4): 282-8. showed an even higher prevalence of abdominal obesity, 54.6%. In comparison with other countries, few studies are found in literature. The values observed in Brazil are the highest reported when compared to rural areas of Nigeria (38.5%)²⁹29. Ogunmola OJ, Olaifa AO, Oladapo OO, Babatunde OA. Prevalence of cardiovascular risk factors among adults without obvious cardiovascular disease in a rural community in Ekiti State, Southwest Nigeria. BMC Cardiovasc Disord 2013; 13: 89. https://dx.doi.org/10.1186%2F1471-2261-13-89
https://dx.doi.org/10.1186%2F1471-2261-1... and Liaoning Province (15.1%)³⁰30. Guo X, Li Z, Guo L, Zheng L, Yu S, Yang H, et al. An update on overweight and obesity in rural Northeast China: from lifestyle risk factors to cardiometabolic comorbidities. BMC Public Health 2014; 14: 1046. https://doi.org/10.1186/1471-2458-14-1046
https://doi.org/10.1186/1471-2458-14-104... .

Household situation was shown to play a determining role in the distribution of outcomes, with differences between genders. In general, higher prevalences of general obesity in urban areas were observed for low- and middle-income countries, such as South Africa (28.0% urban vs. 17.3% rural)³¹31. Atek M, Traissac P, El Ati J, Laid Y, Aounallah-Skhiri H, Eymard-Duvernay S, et al. Obesity and association with area of residence, gender and socio-economic factors in Algerian and Tunisian adults. PloS One 2013; 8(10): e75640. https://doi.org/10.1371/journal.pone.0075640
https://doi.org/10.1371/journal.pone.007... and China (10.6% urban vs. 7.6% rural)³²32. Reynolds K, Gu D, Whelton PK, Wu X, Duan X, Mo J, et al. Prevalence and risk factors of overweight and obesity in China. Obesity (Silver Spring, Md) 2007; 15(1): 10-8. https://doi.org/10.1038/oby.2007.527
https://doi.org/10.1038/oby.2007.527... . In Turkey, however, a strong similarity between the prevalence of obesity between household situations²⁵25. Oguz A, Temizhan A, Abaci A, Kozan O, Erol C, Ongen Z, et al. Obesity and abdominal obesity; an alarming challenge for cardio-metabolic risk in Turkish adults. Anadolu Kardiyol Derg 2008; 8(6): 401-6. (approximately 30% in both cases) was found in adults, but a higher prevalence of obesity in rural areas (39.6% rural vs. 33.4% urban) was reported in the United States²⁴24. Befort CA, Nazir N, Perri MG. Prevalence of obesity among adults from rural and urban areas of the United States: findings from NHANES (2005-2008). J Rural Health 2012; 28(4): 392-7. https://doi.org/10.1111/j.1748-0361.2012.00411.x
https://doi.org/10.1111/j.1748-0361.2012... . In Brazil, in one of the few studies that evaluated household situations in relation to abdominal obesity, a higher prevalence was found in the rural countryside (71.2%) compared to the urban countryside (67.6%) and the metropolitan region (69.5%) of Pernambuco³3. Pinho CP, Diniz A da S, Arruda IK, Batista Filho M, Coelho PC, Sequeira LA, et al. Prevalência e fatores associados à obesidade abdominal em indivíduos na faixa etaria de 25 a 59 anos do Estado de Pernambuco, Brasil. Cad Saúde Pública 2013; 29(2): 313-24. http://dx.doi.org/10.1590/S0102-311X2013000200018
http://dx.doi.org/10.1590/S0102-311X2013... .

The increase in prevalence of obesity in rural areas has been attributed to the modernization of societies, which, among other factors, has led to the improvement of working instruments, mechanization and automation of rural work¹¹11. Malik VS, Willett WC, Hu FB. Global obesity: trends, risk factors and policy implications. Nat Rev Endocrinol 2013; 9(1): 13-27. https://doi.org/10.1038/nrendo.2012.199
https://doi.org/10.1038/nrendo.2012.199... ^,3333. Popkin BM, Adair LS, Ng SW. Global nutrition transition and the pandemic of obesity in developing countries. Nutr Rev 2012; 70(1): 3-21. https://doi.org/10.1111/j.1753-4887.2011.00456.x
https://doi.org/10.1111/j.1753-4887.2011... , also in Brazil⁴4. Dias EC. Condições de vida, trabalho, saúde e doença dos trabalhadores rurais no Brasil. In: Pinheiro TMM, org. Saúde do trabalhador rural - RENAST. Brasília: Ministério da Saúde; 2006. p. 1-27.. A positive association between urbanization and abdominal obesity in adults has been reported in China³⁴34. Inoue Y, Howard AG, Thompson AL, Gordon-Larsen P. Secular change in the association between urbanisation and abdominal adiposity in China (1993-2011). J Epidemiol Community Health 2018; 72(6): 484-90. https://doi.org/10.1136/jech-2017-210258
https://doi.org/10.1136/jech-2017-210258... .

Concomitantly, the so-called nutritional transition has led to a greater caloric intake, with an increase in the consumption of fats, sugar and refined cereals, thus modifying the profile of morbidity and mortality in societies³³33. Popkin BM, Adair LS, Ng SW. Global nutrition transition and the pandemic of obesity in developing countries. Nutr Rev 2012; 70(1): 3-21. https://doi.org/10.1111/j.1753-4887.2011.00456.x
https://doi.org/10.1111/j.1753-4887.2011... . However, trends in urbanization and modernization have different effects between populations in each country, making it impossible to generalize these effects on health at the national or global levels⁶6. Neuman M, Kawachi I, Gortmaker S, Subramanian SV. Urban-rural differences in BMI in low- and middle-income countries: the role of socioeconomic status. Am J Clin Nutr 2013; 97(2): 428-36. https://doi.org/10.3945/ajcn.112.045997
https://doi.org/10.3945/ajcn.112.045997... .

With data from the PNS 2013, the relationship between household situation and the outcomes analyzed differs between genders, and these relations behave differently in each macroregion, with lower prevalences of general obesity among men living in rural areas in the North and Northeast regions, and, for abdominal obesity, lower prevalences in rural areas in all regions. Among women, similar prevalences between household situations were observed across the country. The prevalence of obesity in women was still higher than in men for both rural and urban areas, with an alarming discrepancy in the values for women, mainly for abdominal obesity. Age and parity, as biological conditions, may explain these findings, since they are directly related to weight gain. Socioeconomic and occupational aspects related to the specificities of men and women in rural areas could explain these findings.

The difference in occupations between genders in these regions can also be related to the results, considering that functions that require less physical effort, coinciding with the technological advances, increased mechanized work and less leisure physical activities are known to lead to weight gain¹⁶16. Pinheiro ARO, Freitas SFT, Corso ACT. Uma abordagem epidemiológica da obesidade. Rev Nutr 2004; 17(4): 523-33. http://dx.doi.org/10.1590/S1415-52732004000400012
http://dx.doi.org/10.1590/S1415-52732004... . A study carried out with a cohort of rural workers in Canada³⁵35. Pickett W, Day L, Hagel L, Brison RJ, Marlenga B, Pahwa P, et al. The Saskatchewan Farm Injury Cohort: rationale and methodology. Public Health Rep 2008; 123(5): 567-75. https://dx.doi.org/10.1177%2F003335490812300506
https://dx.doi.org/10.1177%2F00333549081... reported a consistent association between increased participation in mechanized tasks in agricultural work, overweight and obesity³⁶36. Pickett W, King N, Lawson J, Dosman JA, Trask C, Brison RJ, et al. Farmers, mechanized work, and links to obesity. Prev Med 2015; 70: 59-63. https://doi.org/10.1016/j.ypmed.2014.11.012
https://doi.org/10.1016/j.ypmed.2014.11.... . In Brazil, a study carried out in a rural area of Minas Gerais showed a higher concentration of physical activities in men³⁷37. Bicalho PG, Hallal PC, Gazzinelli A, Knuth AG, Velásquez-Meléndez G. Adult physical activity levels and associated factors in rural communities of Minas Gerais State, Brazil. Rev Saúde Pública 2010; 44(5): 884-93. https://doi.org/10.1590/s0034-89102010005000023
https://doi.org/10.1590/s0034-8910201000... , and reports of life habits of these places, when compared to the urban area, include higher consumption of family farming products, higher energy expenditure with physical displacement at work, and intense manual labor, especially during harvest³⁸38. Pinho CP, Diniz A da S, Arruda IK, Lira PI, Sequeira LA, Gonçalves FC, et al. Excesso de peso em adultos do Estado de Pernambuco, Brasil: magnitude e fatores associados. Cad Saúde Pública 2011; 27(12): 2340-50. http://dx.doi.org/10.1590/S0102-311X2011001200006
http://dx.doi.org/10.1590/S0102-311X2011... ^,3939. Little M, Humphries S, Patel K, Dewey C. Factors associated with BMI, underweight, overweight, and obesity among adults in a population of rural south India: a cross-sectional study. BMC Obes 2016; 3: 12. https://doi.org/10.1186/s40608-016-0091-7
https://doi.org/10.1186/s40608-016-0091-... . However, in women, the same study reported lower concentration of physical activity at work, while the domestic domain was the most prevalent³⁷37. Bicalho PG, Hallal PC, Gazzinelli A, Knuth AG, Velásquez-Meléndez G. Adult physical activity levels and associated factors in rural communities of Minas Gerais State, Brazil. Rev Saúde Pública 2010; 44(5): 884-93. https://doi.org/10.1590/s0034-89102010005000023
https://doi.org/10.1590/s0034-8910201000... . Thus, it is possible that our findings are in agreement with the hypothesis that, although technologies currently developed and urbanization induce changes in living standards and food/eating behavior of populations, manual labor in some rural regions may be considered a protective factor for obesity, especially among men.

The socioeconomic determinants, with emphasis on income and schooling, may be related to weight gain in younger age groups and to schooling among women, a fact already consolidated in literature⁴⁰40. Sichieri R, Moura EC. Análise multinível das variações no índice de massa corporal entre adultos, Brasil, 2006. Rev Saúde Pública 2009; 43(Supl. 2): 90-7. http://dx.doi.org/10.1590/S0034-89102009000900012
http://dx.doi.org/10.1590/S0034-89102009... ^,4141. Monteiro CA, Conde WL, Popkin BM. Independent effects of income and education on the risk of obesity in the Brazilian adult population. J Nutr 2001; 131(3): 881S-6S. https://doi.org/10.1093/jn/131.3.881S
https://doi.org/10.1093/jn/131.3.881S... ^,4242. Costa CS, Schneider BC, Cesar JA. Obesidade geral e abdominal em idosos do Sul do Brasil: resultados do estudo COMO VAI? Ciênc Saúde Coletiva 2016; 21(11): 3585-96. http://dx.doi.org/10.1590/1413-812320152111.02492016
http://dx.doi.org/10.1590/1413-812320152... ^,4343. Instituto Brasileiro de Geografia e Estatística. Pesquisa de Orçamentos Familiares 2008-2009: análise do consumo alimentar pessoal no Brasil. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística ; 2011.. In the Brazilian rural area, characterized by low educational level, low income and poor access to health services and research, the population often has health problems neglected⁴4. Dias EC. Condições de vida, trabalho, saúde e doença dos trabalhadores rurais no Brasil. In: Pinheiro TMM, org. Saúde do trabalhador rural - RENAST. Brasília: Ministério da Saúde; 2006. p. 1-27.. Unschooled or incomplete elementary school students represent 44.2% of urban inhabitants and 79.6% in rural areas, according to the latest census⁴⁴44. Instituto Brasileiro de Geografia e Estatística. Censo demográfico 2010: Trabalho e rendimento. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística ; 2010.. Also, the relation between occupation and schooling reported in the same census⁴⁴44. Instituto Brasileiro de Geografia e Estatística. Censo demográfico 2010: Trabalho e rendimento. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística ; 2010. is highlighted, as the group of lower educational level 78.3% of individuals self-declared as “skilled in agricultural, forestry, hunting and fishing”⁴⁴44. Instituto Brasileiro de Geografia e Estatística. Censo demográfico 2010: Trabalho e rendimento. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística ; 2010., occupations typical of rural areas. The same has already been demonstrated by a study with agricultural workers in Brazil, which concluded that these activities are performed mostly by men at younger age, non-white skinned, with lower level of schooling and income, and living in regions with the worst social and health indicators of the country⁴⁵45. Moreira JPL, Oliveira BLCA, Muzi CD, Cunha CLF, Brito AS, Luiz RR. A saúde dos trabalhadores da atividade rural no Brasil. Cad Saúde Pública 2015; 31(8): 1698-708. http://dx.doi.org/10.1590/0102-311X00105114
http://dx.doi.org/10.1590/0102-311X00105... , factors that are also associated with obesity. Thus, disparities between rural and urban areas can be justified by the relationship between educational and socioeconomic levels in each macroregion.

The literature has already shown that mean BMI in less developed countries is generally higher in urban areas than in rural areas⁶6. Neuman M, Kawachi I, Gortmaker S, Subramanian SV. Urban-rural differences in BMI in low- and middle-income countries: the role of socioeconomic status. Am J Clin Nutr 2013; 97(2): 428-36. https://doi.org/10.3945/ajcn.112.045997
https://doi.org/10.3945/ajcn.112.045997... , but the extent of the association between urban area and BMI is substantially reduced after adjusting for socioeconomic status, suggesting the importance of these factors to understand this association⁶6. Neuman M, Kawachi I, Gortmaker S, Subramanian SV. Urban-rural differences in BMI in low- and middle-income countries: the role of socioeconomic status. Am J Clin Nutr 2013; 97(2): 428-36. https://doi.org/10.3945/ajcn.112.045997
https://doi.org/10.3945/ajcn.112.045997... . After the inclusion of the variables marital status, schooling and income, the latter considered a proxy for socioeconomic level, the results showed an association between residing in rural areas and abdominal obesity only for the Northeast Region among both men and women. Regarding general obesity, there was a change in the measure of effect, but not in statistical significance, suggesting that the economic disparity is an important element when it comes to differences in prevalence related to household situation, especially with regard to the Northeast Region. Further research exploring the linkage of socioeconomic variables and specificities of economic factors in rural areas may provide important information to explain the associations observed here.

The limitations of this study include the lack of data on the current degree of mechanization and urbanization in rural areas of Brazil, which may influence the process of epidemiological transition characterized by changes in nutrition and consumption pattern that accompany changes in the economic, social, demographic and health profile of the population⁴⁶46. Popkin BM, Keyou G, Zhai F, Guo X, Ma H, Zohoori N. The nutrition transition in China: a cross-sectional analysis. Eur J Clin Nutr 1993; 47(5): 333-46.. This variable could further support the explanation of lower prevalence of obesity among men living in rural regions with physical labor. However, the present study was the largest one ever carried out in the country, with a representative sample, and one of the few that aimed to explore the relationship with household situation. In addition, the advantage of anthropometric measurements has been verified.

CONCLUSION

Finally, the present study shows a clear heterogeneity in the prevalence of general and abdominal obesity between the regions studied. In general, lower values were found among men living in rural areas in all regions. On the other hand, it is suggested that living in rural areas may have a negative impact on the health of women with regard to general and abdominal obesity, especially highlighting the greater difference in abdominal obesity found in this household situation compared to men, which places this group at higher risk for cardiovascular diseases and other health problems.

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