Prevalence of Overweight and Associated Factors in a Male Prison Population in the Extreme South of Brazil: A Cross-Sectional Study

Abstract

Background:

This cross-sectional study serves as a first Brazilian inventory about overweight as a marker for metabolic health and risk factor to develop noncommunicable chronic diseases in prison populations. The prevalence of overweight, and its associated factors in prisoners of the Fifth Regional State Penitentiary of Rio Grande do Sul (5th DPR) in the extreme South of Brazil were investigated using a precoded questionnaire with sociodemographic, behavioral, and health questions, applied to proportional stratified random sampled prisoners.

Methods:

Five hundred eighty male prisoners (70%) in the closed regime agreed to answer the questionnaire and allowed anthropomorphic body measurement, carried out by trained scientists. We used bivariate Pearson's chi-squared test and adjusted multinomial logistic regression for analyses.

Results:

Considering that the studied incarcerated population is young (mean age 33 years) it is concerning that already 43.6% of them are overweight, report regular sweets and sugary soft drink consumption (77.7%, and 81.4%, respectively), 60.2% are smokers, and 19.4% are at elevated risk to develop cardiovascular diseases. Further, 13.8% of the respondents reported a diagnosis of hypertension, 4.9% hypercholesterolemia, and 2.7% diabetes mellitus type 2. Among those who reported not smoking, excess weight was almost four times higher (prevalence ratio: 3.79; 95% confidence interval: 2.61–5.50).

Conclusions:

Our study suggests that the prison environment promotes modifiable risk factors for chronic diseases. These data deserve attention and intervention, aiming to prevent and reduce the current levels of excess weight.

Introduction

The health of the prison populations has been the subject of only a few studies, even though there are more than 10 million people in prison worldwide.¹ With currently more than 700,000 prisoners, Brazil occupies the third largest prison population in the world, behind China and the USA.² In a total of capacities in 2776 prison establishments the country counts a deficit of over 240,000 prisoner's accommodations.² The prison reality of the Brazilian state Rio Grande do Sul is no different from the national one, where there exist 21,444 prisoner's accommodations for 31,484 prisoners; that is, a deficit of 10,040 accommodations.

These prisons are permanently overcrowded, housing inmates in humid, dark and poorly ventilated rooms, lacking hygienic support, and health care. As a consequence, infectious diseases like tuberculosis are 30 times higher in Brazilian prisons, than in the local non-prison population.³ In addition to these poor conditions, confinement itself and the accumulation of risk factors such as smoking, physical inactivity, and poor diet, worsen the nutritional state contributing to overweight in detainees. As overweight is one of the main risk factors for noncommunicable chronic diseases (NCDs) it will be in the focus of this article.^4
–6

NCDs are multifactorial diseases that develop throughout life, being responsible for more than 72% of the causes of deaths in Brazil. Arterial hypertension, type 2 diabetes mellitus (DM2), obesity, hypercholesterolemia [the main risk factor for cardiovascular diseases (CVDs)], and depression are the most prevalent NCDs in the country.⁷ About 40% of the adult Brazilian population, equivalent to 57.4 million people, suffer from at least one NCD, and more than half of the population is overweight, according to data from the national report Vigitel 2018.⁸

Overweight and the presence of NCDs in the prison population is not only a matter of cost to the public health system but also affects healthy life span allowing people to work and support their families and hinders social reintegration after prison.

Although the high prevalence of NCDs, especially obesity, in the Brazilian population is widely known, studies on the epidemiological situation in the context of inmates were not found by our group. Most studies concerning this population address infectious diseases and mental disorders, leaving NCDs untouched.^9
–11

Thus, our study aimed to find out the prevalence of people living with overweight and obesity, and which overweight-related NCDs and risk factors are prevalent in the prison population. Detailed information about the health status of prisoners will allow creating specific health care protocols and direct subsidies tailored to the needs of its target population.

Subjects and Methods

Study design and participants

This is a cross-sectional study developed as part of a larger project, whose objective was to assess the general health of the prison population of the Fifth Regional State Penitentiary of Rio Grande do Sul (5th DPR). This included the state prisons of the municipalities of Camaquã, Canguçu, Jaguarão, Pelotas, Rio Grande, and Santa Vitória do Palmar. The data were collected from April to December 2017. At the time, these penitentiaries counted ∼2614 inmates, 1407 of whom were in the closed regime. This number was provided by the annual report of “Superintendência dos Serviços Penitenciários” (SUSEPE—Superintendence of Penitentiary Services) from 2016¹⁰ and was used for the sample calculation, including prisoners in a closed regime and excluding those who had either cognitive limitation or mental disorders that disabled them from understanding the questions asked.

Sample calculation

The sample calculation was performed using the program Epiinfo 7.0. The expected overweight frequency used was 25% with a margin of error of 5% and a confidence level of 95% (N = 288), which, after addition of 10% for losses totaled 317 individuals. For the calculation of the associated factors, a prevalence of outcome equal to 25%, a confidence level of 95%, a relative risk of 2.0, and a statistical power of 80% were used, adding 10% for losses, 20% for confounding factors, and 50% design effect. Due to the lack of specific information about Brazilian prison populations, the associated factors were copied from the annual SUSEPE bulletin,¹⁰ namely age over 35, incomplete elementary school, absence of a partner, and white skin color.

As the sample number for the associated factors required a larger number of individuals, we decided to use the highest N for the study (N = 755), corresponding to the risk factor “Incomplete fundamental study.” These 755 interviews were distributed according to prison's inmate prevalence: 309 (41%) interviews in the prison of Pelotas; 242 (32%) in Rio Grande; 121 (16%) in Camaquã, 32 (4.5%) in Jaguarão; 26 (3.4%) in Canguçu and 25 (3.3%) in Santa Vitória do Palmar. Due to the population size and logistics of each prison, stratified random proportional sampling was performed, through the inmate lists provided by each prison, and a jump of three was used to draw lots for the interviewed prisoners.

Instruments

A standardized and precoded questionnaire¹² was used with the variables: age in complete years, self-reported skin color (white, non-white), education in complete years (≤7 and >8), marital status (single or with partner), family income (divided into minimum wages of 937,00 Brazilian Reals in 2017), frequency of physical activity (more or <150 min duration/week, as defined by the WHO¹³), tobacco use (in the last 6 month yes and no, even when occasionally¹⁴), prison time (≤30 months and ≥31 months), work in prison (yes or no), receiving visits (yes or no), sweets consumption (yes and no, yes meaning at least 1 day/week), soft drink consumption (yes and no, yes meaning at least 1 day/week), replacement of meal served in the prison (yes and no), presence of self-reported NCD of hypertension, DM2, and hypercholesterolemia (yes or no), and risk for CVD according to the waist circumference (WC >94 cm).¹⁵ The International Neuropsychiatric Mini Interview (MINI Plus), validated for the Brazilian population, was used to assess the presence of depression and anxiety.¹⁶ All participants signed an informed consent form.

The outcome was obtained through anthropometric variables of weight and height, determining excess weight through the body mass index (BMI = weight/height²). Inmates were classified according to the WHO 2000 reference, classifying BMI >25 as overweight.¹⁷ Anthropometric measurements of weight, height, and WC were collected by the interviewers, at the location provided in each prison, using a portable scale with 100 grams precision for up to 150 kg and an inextensible measuring tape. As suggested by the WHO, we included WC into our questionnaire due to its additional information about abdominal adiposity of the individual. Increased visceral adipose tissue is associated with a range of metabolic abnormalities, including decreased glucose tolerance, reduced insulin sensitivity, and adverse lipid profiles, which are risk factors for type 2 diabetes and CVD.¹⁵

Statistical analysis

All questionnaires were coded and revised by the interviewers and entered twice in reverse order, by different typists using the Epi-Info 7.0 program. Data analysis was performed using IBM SPSS (version 20.0; IBM Corp., Armonk, NY). For bivariate analysis of the sample, the prevalence ratio (PR), 95% confidence intervals (CIs), and Pearson's chi-squared test were calculated, adopting a P value <0.05 of a two-tailed test. For the adjusted analysis, multinomial logistic regression was performed, according to a three-level hierarchy model, for causal effects. The first and most distal level comprised demographic and socioeconomic variables. Variables associated with prison conditions were included in the second level. At the third level, the most proximal, variables related to eating habits and NCD history were included. Variables with P < 0.20 in the bivariate analysis and those that maintained P ≤ 0.005 were included in the model.

Study registration

The project complies with the ethical principles contained in the Declaration of Helsinki and was approved by the Ethics Committee in the sector of Health Research at the Faculty of Medicine of the Federal University of Rio Grande (CEPAS/FURG) under report number 157/2016.

Results

General characterization of participants

Of the 755 inmates drawn, 175 refused to answer, totaling 580 (77%) of interviewed individuals. The main characteristics are summarized in Table 1. The prevalence of overweight among inmates was 46.3%, while 52.5% were of normal weight and 1.2% were underweight. The average age was 33 [standard deviation (SD) ±9] complete years, 61.6% declared themselves as “white,” 63.4% had no partner, 65.1%, had up to 7 years of school education, and 72% reported a family income less than or equal to a minimum wage (R$ 937.00). Regarding prison issues, 60% of the sample had been in prison for more than 2.5 years, 38.5% worked in the prison and the most frequent reason for arrest was drug trafficking with 35%.

Table 1.

Sociodemographic Data and Prevalence of Overweight in a Male Prison Population in the Extreme South of Brazil

Characteristics	Responses		BMI ≥25		Adjusted analysis
Characteristics	N	%	N	%^a	PR	95% CI
Age, years	(570)		P < 0.001		P < 0.001
≤25	126	22.1	44	34.9	1.0
26–35	258	45.3	107	41.5	2.22	1.50–3.30
≥36	186	32.6	113	70.8	2.80	1.73–4.53
Skin color	(554)		P = 0.531
White	341	61.6	163	47.8
Non-white	213	38.4	96	45.1
Marital status	(569)		P < 0.001		P < 0.001
Single	361	63.4	145	40.2	1.0
With partner	208	36.6	119	57.2	1.88	1.32–2.68
Education, years	(564)		P = 0.185		P = 0.119
≤7	367	65.1	163	44.4	1.0
≥8	197	34.9	99	50.3	0.75	0.525–1.07
Family income, MW	(570)		P = 0.371
≥1.1	137	24.0	68	49.6
≤1	433	76.0	96	45.3
Prison time, months	(562)		P = 0.054		P = 0.573
≤30	360	64.1	155	43.1	1.0
≥31	202	35.9	104	51.5	0.89	0.62–1.30
Prison work	(567)		P < 0.001		P = 0.001
Yes	218	38.4	126	57.8	1.81	1.26–2.61
No	349	61.6	138	39.5	1.0
Visit in prison	(569)		P = 0.258
Yes	405	71.2	194	47.9
No	164	28.8	70	42.7

MW (R$ 937.00 in 2017), BMI (WHO).

Percentage of obesity inside the subgroup.

BMI, body mass index; MW, minimum wage; PR, prevalence ratio.

Diseases and behavioral habits

Regarding health issues and self-reported diseases (Table 2), 19.4% had an increased risk for CVD with WC >94 cm, 13.8% reported a diagnosis of hypertension, 4.9% of hypercholesterolemia, and 2.7% of DM2. Referring to these pathologies, 6.7%, 2.1%, and 1.7%, respectively, used drugs. In addition, 17.6% had symptoms for anxiety and 18.4% depression. Regarding behavioral habits, 60% used tobacco and 78.1% reported having already used some type of drug, mainly 63.4% marijuana and 7% cocaine. More than 60% (367) of the sample reported practicing physical activity in the prison. Of these, 261 (45%) are considered physically active according to the WHO criterion of >150 min/week, while 36% did not practice any type of physical activity. In terms of alimentation, 64% answered never to replace the meals served in the prison with another food and 6% replace it every day. Another 20% reported consuming fruits and vegetables daily, 78.2% and 81.7% reported consuming sweets and soft drinks, respectively.

Table 2.

Prevalence of Non-Communicable Chronic Diseases and Behaviors Associated to Obesity and Overweight of the Study Population

Characteristics	Responses		BMI <25		Adjusted analysis
Characteristics	N	%	N	%^a	PR	95% CI
CVD risk^b	566		P < 0.001		P < 0.001
WC <94 cm	456	80.6	153	33.6	1.0
WC ≥94 cm	110	19.4	109	99.1	170.57	23.15–1256.58
Self-reported hypertension	555		P < 0.001		P = 0.003
Yes	77	13.9	55	71.4	2.93	1.45–5.95
No	478	86.1	204	42.7	1.0
DM2	554		P = 0.034		P = 0.559
Yes	15	2.7	11	73.3	1.58	0.34–7.37
No	539	97.3	246	45.6	1.0
Hypercholesterolemia	559		P = 0.082		P = 0.236
Yes	27	4.8	17	63.0	0.41	0.09–1.77
No	532	95.2	244	45.9	1.0
Depression	570		P = 0.599
Yes	107	18.8	52	48.6
No	463	81.2	212	45.8
Anxiety	579		P = 0.880
Yes	100	17.5	47	47.0
No	470	82.5	217	46.2
Physically active^c	569		P = 0.115		P = 0.149
Yes	360	63.3	158	43.9	1.0
No	209	36.7	106	50.7	1.32	0.90–1.94
Smoking	568		P < 0.001		P < 0.001
Yes	342	60.2	112	32.7	1.0
No	226	39.8	152	67.3	3.79	2.61–5.50
Replacement of meals	568		P = 0.470
Yes	202	35.6	98	48.5
No	366	64.4	166	45.4
Sweets consumption	569		P = 0.755
Yes	443	77.7	204	46.0
No	126	22.3	60	47.6
Soft drink	569		P = 0.057		P = 0.741
Yes	463	81.4	206	44.5	0.90	0.49–1.64
No	106	18.6	58	54.7	1.0

Percentage of overweight inside the subgroup.

WC ≥94 cm defined as high risk for CVDs.

Greater than or equal to 150 min/week as defined as a physically active individual.

CVD, cardiovascular disease; DM2, type 2 diabetes mellitus; WC, waist circumference.

The bivariate analysis, revealed that being overweight has a higher prevalence in people older than 26 years, with a partner, who work in prison, are non-smokers, with a WC ≥94 cm, who reported having hypertension and DM2.

In the adjusted analysis, we observed that an age between 26 and 35 years doubles (PR: 2.22; 95% CI: 1.50–3.30) the chances of being overweight, while it almost triples in individuals passing 36 years (PR: 2.80; 95% CI: 1.73–4.53) compared to prisoners aged 25 or less. Those who reported having a partner or working in prison were 88% and 81%, respectively, more likely to be overweight than those without a partner and without a job. While among those who reported not smoking, excess weight was almost four times higher (PR: 3.79; 95% CI: 2.61–5.50) than among smokers. WC ≥94 cm was the factor most associated with excess weight (PR: 170.57; P value <0.001). Inmates with a history of systemic arterial hypertension were three times more overweight (PR: 2.93; 95% CI: 1.45–5.95) than those who denied having the pathology, which is in line with the knowledge about obesity as a risk factor for CVDs.

Discussion

Obesity is considered one of the main risk factors for developing NCDs or a sudden cardiovascular event. In the present study, we analyze the prevalence of being overweight and associated risk factors to develop NCDs to assess the general health of the prison population of the extreme South of Brazil. We found that nearly half of the prisoners are overweight and the prevalence of tobacco use and sugary foods consumption is high. Further, obesity was associated with other risk factors for NCDs, such as hypertension, smoking habits, WC ≥94 cm, and consumption of soft drinks and sweets.

In fact, finding 46.3% overweight prisoners is not unexpected, considering that 67% of the regional male population is overweight too.⁸ But we like to stress that the average age of the sample is 33 years (SD ±9), which is younger than the local comparison group. In line with the latest national survey in Brazil is also the significant increase of the prevalence of being overweight in men of the free population (35–44 years),⁸ and prisoners aging ≥36 years that presented a more than three times higher chance to be overweight. In international studies with prison populations, however, no significant differences were found between the age groups.¹⁸ When comparing available international prison populations, prisoners' overweight records range from 26.5% in a study from Africa to 77% in a U.S. study.^19,20 This high range of variability is associated with the prevalence of being overweight in the free population of each county. Besides, the socioeconomic and cultural differences of these specific locations, the different forms of data collection for calculating BMI (measured vs. self-reported), may underestimate the prevalence found.^21,22

Unhealthy diet and insufficient physical activity are the main contributors to development of overweight and its associated morbidities. Confinement comes with drastic restrictions for both, reducing options of food choice and physical activity in terms of daily routine walks (e.g., to work place, supermarket, etc.). In this context, it is concerning that 78.2% and 81.7% reported regular consumption of sweets and sugar added soft drinks, while only 20% reported to consume fruits or vegetables daily. Furthermore, the number of 45% physically active prisoners is comparable to what was reported from six other international prison studies.¹⁸ This means that half of the prisoners are not sufficiently physically active or practice no sport at all (36%). A habit that is especially for a young population not healthy. For better comparison, we suggest to include questions about time spent sedentary into future questionnaires, questions that were recently also added to the yearly occurring Brazilian survey, Vigitel.¹¹ And further, we should rethink whether the WHO definition of a “physically active person” is adequate to describe the activity level of an individual that has such a reduced action radius like prisoners.

In addition to age, the report of “having a partner” showed an 88% probability of being overweight. Although we do not find data on this variable in the literature, we believed that the fact of having a partner may increase the chances of receiving food outside the prison system, due to the higher frequency of visits and even the offer of processed foods. In the general population of this region, studies have shown that individuals who lived with a partner were 1.3 times more likely to be overweight when compared to those who lived alone.^23,24

Another factor associated with being overweight was “working in the prison.” Men who reported having a job in the prison unit were 81% more likely to be overweight than those who did not work. It is believed that prison work may allow greater contact with food, since most of these individuals worked in the prison's kitchen. Detainees are also believed to use work, such as cleaning, in exchange for unhealthy food, such as sweets, with other inmates who receive this food from outside the prison during visitations. No studies were found that address this type of data.

Another risk factor associated to being overweight and development of NCDs is the use of drugs, including alcohol. In contrast, smokers tend to be less overweight than their peers. The present study revealed that 60.2% of prisoners are smokers, which is higher than the 14.4% of smokers reported from the general population in Rio Grande do Sul.⁸ The high prevalence of tobacco use is also known from other international prison studies, like in Australia (57% smokers) and Spain (70%).^24,25 The ban on the use of alcohol and drugs in prisons may explain the increase in smoking and even increase the intake of sweets as an unconscious compensation mechanism.^26,27 However, despite the high consumption of tobacco in the population studied, it was observed that those who did not smoke were four times more overweight than smokers. Considering that the studied population comprises a substantial proportion of young men deprived of their liberty, this behavior probably affects long-term metabolic health of this population.

The prevalence of NCDs in prisons varies between countries and, sometimes even within countries, as well as between sexes. The present study found a prevalence of 13.8% for arterial hypertension, 4.9% for dyslipidemia, and 2.7% for diabetes mellitus. The values found in this research are lower than those found in the Brazilian population. According to data from the Brazilian national survey 2018,⁸ 22.1% of Brazilians suffer from hypertension and 7.1% have DM2. However, our sample consists predominantly of young adults, therefore, it was expected to find a lower prevalence of already established metabolic diseases. A study carried out in Mexico, with 15,000 prisoners, found a prevalence of 2.8 for hypertension and 2.8% for DM.²⁸ In a study carried out in Australia with 121 men deprived of their liberty, the prevalence of hypertension was 26.7% and 5% of diabetes.²⁹ Additionally, it is observed that among prisoners who reported hypertension, excess weight was three times greater than among those who denied having the disease, confirming obesity as a risk factor for hypertension.

As expected, excess weight among prisoners of this study was highly associated with “waist circumference greater than 94 cm.”¹⁵ With this additional anthropometric measure we made sure that prisoners with an BMI ≥25 are overweight due to abdominal adiposity and not because of excessive gym activities, as reported from other prisons.²² Excess weight, increased WC, and hypertension are well established risk factors for the development of CVDs.⁷ In that meaning, a recent Nature review from Ross et al assign WC an even more important role as a tool to identify the high-risk obesity phenotype.³⁰ While a study carried out in a Spanish prison, with 99 prisoners, found that 10% of the prisoners had an increased risk of suffering from CVDs²¹ we report here that 19.6% of present study group belong to that category and advise to include WC in future studies for better comparison and monitoring.

Among the limitations of the present study, is its cross-sectional study design, where results and exposures are collected at the same time, and findings can be affected by reverse causality bias. Therefore, the associations identified should not be interpreted as causal relationships. Further, the lack of clinical data (e.g., blood analysis) and reliance on self-reported perceptions of the prisoners might influence the outcome of our study. Furthermore, most studies published on incarcerated populations come from developed countries, with a different prison structure and with a focus on communicable and infectious diseases. Therefore, the strength of this study is that it presents a first description of the prevalence of NCDs and their risk factors in South Brazilian prisons. In addition, we highlight that our measures to assess excess weight, one of the main risk factors for NCDs, were made by trained scientists and not self-reported as in most studies, to obtain more reliable data.

Conclusions

Considering that the surveyed prison population on average is young, we describe here a risk group for being overweight and perhaps CVDs that will affect current inmates only in their future. Therefore, we suggest that the health status of those prisoners older than 36 years, with overweight, with a WC >94 cm, and/or with hypertension should be monitored frequently from the health system. We like to emphasize the importance of these findings, since, in general, Brazilian prisoners are released, on average, after 7 years in prison and the NCDs caused by excess weight will appear more likely when they are at liberty.

Footnotes

Acknowledgments

The authors acknowledge the assistance of all participating prison institutions and the prisoners, without whose support this research would not have been possible. We acknowledge the help and support of all the named federal prison administration teams, and additional staff who assisted on a temporary basis.

Author's Contributions

A.R.M., L.C.d.R.A., D.P.M., N.R.F., R.C.L., and J.S.V., I.B.R. and F.A.d.A.G. were responsible for data collection in the prisons. I.S., C.C.B., R.A.M.S., C.V.G., and V.P.d.H. contributed to study design, statistical analysis, and data interpretation. All authors have read and approved the final version of the article, and agree with the order of presentation of the authors.

Author Disclosure Statement

No conflicting financial interests exist. The funding source had no influence on research conduct, data analysis, interpretation and writing.

Funding Information

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001.

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