Increasing trends in obesity prevalence from 2013 to 2019 and associated factors in Brazil

Ferreira, Arthur Pate de Souza; Szwarcwald, Célia Landmann; Damacena, Giseli Nogueira; Souza Júnior, Paulo Roberto Borges de

doi:10.1590/1980-549720210009.supl.2

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Revista Brasileira de Epidemiologia

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ORIGINAL ARTICLE • Rev. bras. Epidemiol. 24 (suppl 2) • 2021 • https://doi.org/10.1590/1980-549720210009.supl.2 copy

Increasing trends in obesity prevalence from 2013 to 2019 and associated factors in Brazil

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT:

Objective:

To investigate the variation of anthropometric indicators from 2013 to 2019 and the factors associated with obesity in Brazil, using information from the National Health Survey.

Methods:

Cross-sectional study with cluster sampling and simple random sampling in the three stages. Measurements of weight and height among participants in 2013 (n=59,592) and in 2019 (n=6,672) were used. Differences in obesity prevalence were tested by Student’s t test for independent samples. To identify the sociodemographic factors and health problems associated with obesity, we used Poisson regression models with robust variance and crude and age-adjusted prevalence ratios to test the associations.

Results:

From 2013 to 2019, prevalence of obesity increased significantly, from 20.8 to 25.9%. Among men, the greatest increases were found in the 40-59 age group (9.1%) and in the median income category (8.3%). Among women, the greatest rises were found among those with low education (8.7%) and non-white ones (6.0%). For both males and females, factors associated with obesity were age, to live with a partner, level of instruction directly associated among men, and inversely associated among women. In 2019, for males, the crude and adjusted prevalence ratios were significant for high cholesterol, high blood pressure and at least one chronic non-communicable disease and, for females, for poor self-rated health, high blood pressure, diabetes, and at least one chronic non-communicable.

Conclusion:

It is necessary to implement intersectoral policies to promote changes in eating habits and encourage the practice of physical activity, taking into account economic, social, cultural, and environmental aspects.

Keywords:
obesity; noncommunicable diseases; health surveys; body mass index; Brazil

		2013			2019
		n	%	95%CI	n	%	95%CI
Gender	Male	28,357	47.6	46.8–48.4	3,125	46.8*	45.1–48.6
Gender	Female	31,235	52.4	51.6–53.2	3,547	53.2*	51.4–54.9
Age range	18–39	28,128	47.2	46.4–48.0	2,875	43.1*	40.8–45.4
	40–59	20,593	34.6	33.9–35.2	2,355	35.3	32.3–38.4
	60 or +	10,870	18.2	17.7–18.8	1,442	21.6*	19.6–23.8
Education level	1	23,341	39.2	38.3–40.0	2,315	34.7*	32.8–36.6
	2	9,238	15.5	15.0–16.1	965	14.5	12.7–16.4
	3	27,012	45.3	44.4–46.2	3,392	50.8*	48.2–53.5
Color/race	White	28,339	47.6	46.7–48.4	2,815	42.2*	39.2–45.3
Color/race	Non-white	31,253	52.4	51.6–53.3	3,857	57.8*	54.7–60.8
Living with a partner	Yes	36,403	61.1	60.3–61.8	4,168	62.5	59.6–65.3
Living with a partner	No	23,189	38.9	38.2–39.7	2,504	37.5	34.7–40.4
Living área	Urban	51,367	86.2	85.7–86.7	5,767	86.4	85.2–87.6
Living área	Rural	8,225	13.8	13.3–14.3	905	13.6	12.4–14.8
Per capita income	<1 MW	29,587	49.6	48.7–50.6	3,364	50.4	47.8–53.0
	≥1 and <2 MW	17,217	28.9	28.2–29.6	1,999	30.0	27.6–32.4
	>2 MW	12,788	21.5	20.6–22.4	1,310	19.6	17.4–22.0

		2013			2019
		n	%	95%CI	n	%	95%CI
Poor health self-assessment		19,248	32.3	31.6–33.0	2,236	33.5	31.0–36.1
High cholesterol		7,480	12.6	12.1–13.0	967	14.5*	13.2–15.9
Heart disease		2,488	4.2	3.9–4.5	341	5.1*	4.3–6.0
Hypertension		12,833	21.5	20.9–22.2	1,586	23.8*	22.0–25.6
Diabetes		3,741	6.3	5.9–6.6	548	8.2*	7.2–9.4
Any NCD		26,946	45.2	44.5–46.0	3,450	51.7*	49.6–53.8
Nutritional status	Obesity	12,399	20.8	20.2–21.4	1,728	25.9*	22.6–29.5
	Overweight	33,946	57.0	56.2–57.8	4,024	60.3*	58.2–62.4
	Eutrophy	24,162	40.5	39.8–41.3	2,443	36.6*	34.5–38.8
Mean weight (kg)	T	59,592	71.3	71.1–71.6	6,672	73.5*	72.1–74.9
	M	31,235	76.1	75.7–76.4	3,125	78.3*	77.3–79.3
	F	28,357	66.9	66.7–67.3	3,547	69.3*	67.1–71.5
Mean height (cm)	T	59,592	164.2	164.0–164.3	6,672	164.7*	164.4–165.1
	M	31,235	170.8	170.7–171.0	3,125	171.6*	171.2–172.1
	F	28,357	158.1	158.0–158.3	3,547	158.7*	158.2–159.2

	Male				Female
	2013		2019		2013		2019
	%	95%CI	%	95%CI	%	95%CI	%	95%CI
T	16.8*	16.0–17.7	21.8*	18.7–25.2	24.4*	23.6–25.3	29.5*	25.3–34.2
Age range
1	13.5	12.5–14.5	15.5	12.5–19.2	18.7	17.5–19.8	23.4	16.6–31.8
2	21.1*	19.6–22.7	30.2*	24.7–36.3	30.2*	28.7–31.8	38.0*	32.4–43.9
3	17.9	15.8–20.2	21.2	15.5–28.1	27.5	25.7–29.4	27.5	23.0–32.5
Education level
1	15.0	13.9–16.3	17.8	14.2–22.1	28.8*	27.4–30.2	37.5*	32.8–42.5
2	15.4	13.4–17.6	28.5	15.2–47.2	24.3	22.3–26.5	24.9	19.3–31.5
3	19.0	17.7–20.4	22.4	19.2–26.1	20.9	19.8–22.1	25.5	19.9–32.1
Color/race
W	19.2*	17.9–20.6	24.6*	20.7–29.0	25.0	23.8–26.2	29.1	24.2–34.5
NW	14.7*	13.7–15.8	19.8*	15.6–24.8	23.9*	22.9–25.0	29.9*	25.4–34.8
Living with a partner
Y	19.4*	18.4–20.5	24.9*	21.0–29.1	26.5	25.4–27.6	32.0	26.1–38.7
N	12.1	11.0–13.3	14.3	11.0–18.5	21.6*	20.4–22.8	26.4*	22.6–30.6
Living área
U	17.9*	16.9–18.9	23.1*	19.6–26.9	24.8	23.9–25.7	29.8	25.0–35.1
R	10.8*	9.4–12.3	14.1*	11.7–16.8	21.9*	20.0–24.0	27.7*	24.2–31.5
Per capita income
1	13.1	12.1–14.2	16.3	12.6–20.7	24.5*	23.4–25.6	30.1*	25.7–34.8
2	18.0*	16.4–19.6	26.3*	21.7–31.4	26.2	24.6–27.9	27.0	21.1–33.9
3	22.9	21.0–25.0	23.4	18.0–29.9	21.9	20.3–23.6	25.7	18.5–34.6

	Male				Female
	2013		2019		2013		2019
	PR	95%CI	PR	95%CI	PR	95%CI	PR	95%CI
Age range
1	1.00	–-	1.00	–	1.00	–	1.00	–
2	1.56*	1.42–1.73	1.94*	1.46–2.59	1.62*	1.50–1.75	1.62*	1.23–2.14
3	1.33*	1.15–1.53	1.36	0.96–1.94	1.47*	1.34–1.62	1.18	0.78–1.77
	PR**	95%CI	PR**	95%CI	PR**	95%CI	PR**	95%CI
Education level
1	0.69*	0.61–0.77	0.65*	0.49–0.86	1.23*	1.14–1.33	1.45*	1.18–1.79
2	0.81*	0.69–0.94	1.23	0.70–2.17	1.15*	1.04–1.28	0.97	0.70–1.35
3	1.00	–	1.00	–	1.00	–	1.00	–
Color/race
W	1.28*	1.16–1.41	1.20	0.91–1.57	1.02	0.95–1.08	0.96	0.83–1.11
N	1.00	–	1.00	–	1.00	–	1.00	–
Living with a partner
1	1.53*	1.38–1.70	1.62*	1.19–2.21	1.27*	1.18–1.36	1.25*	1.02–1.52
2	1.00	–	1.00	–	1.00	–	1.00	–
Living area
U	1.69*	1.45–1.95	1.65*	1.31–2.09	1.13*	1.03–1.24	1.07	0.86–1.34
R	1.00	–	1.00	–	1.00	–	1.00	–
Per capita income
1	1.00	–	1.00	–	1.00	–	1.00	–
2	1.36*	1.20–1.53	1.61*	1.24–2.08	1.04	0.96–1.12	0.85	0.66–1.10
3	1.72*	1.53–1.93	1.38	0.96–2.00	0.85*	0.78–0.93	0.81	0.61–1.08

	Male				Female
	2013		2019		2013		2019
	PR	PR**	PR	PR**	PR	PR**	PR	PR**
Poor health self-assessment	1.20*	1.15*	1.01	0.88	1.28*	1.29*	1.35*	1.50*
95%CI	1.12–1.27	1.04–1.28	0.78–1.19	0.71–1.10	1.23–1.33	1.19–1.39	1.21–1.46	1.25–1.80
High cholesterol	2.04*	1.93*	1.47*	1.36*	1.48*	1.34*	1.16	1.08
95%CI	1.80–2.30	1.70–2.19	1.12–1.94	1.02–1.82	1.38–1.60	1.24–1.45	0.90–1.49	0.80–1.47
Heart disease	1.24*	1.08	1.26	1.12	1.39*	1.23*	1.19	1.14
95%CI	1.01–1.52	0.88–1.34	0.81–1.96	0.71–1.77	1.23–1.58	1.08–1.40	0.83–1.71	0.81–1.61
Hypertension	2.35*	2.38*	2.20*	2.16*	2.03*	1.98*	1.72*	1.84*
95%CI	2.13–2.59	2.13–2.66	1.76–2.75	1.66–2.81	1.91–2.16	1.84–2.13	1.44–2.05	1.45–2.33
Diabetes	2.06*	1.86*	1.38	1.24	1.75*	1.54*	1.58*	1.51*
95%CI	1.76–2.42	1.58–2.20	0.90–2.13	0.80–1.91	1.61–1.91	1.40–1.69	1.25–2.00	1.12–2.03
Any NCD	1.71*	1.65*	1.58*	1.48*	1.68*	1.57*	1.50*	1.50*
95%CI	1.55–1.89	1.48–1.83	1.21–2.04	1.12–1.96	1.56–1.80	1.46–1.69	1.15–1.97	1.19–1.89

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[1] Corresponding author: Arthur Pate de Souza Ferreira. Avenida Brasil, 4365, Manguinhos, CEP: 21040-360, Rio de Janeiro (RJ), Brasil. E-mail: arthurpaterj@gmail.com