Literature DB >> 33206881

Can the municipal social deprivation index influence the time trend of the leprosy detection rate?

Carlos Dornels Freire de Souza1, Victor Santana Santos2, Joilda Silva Nery3, Tânia Rita Moreno de Oliveira Fernandes4, Mônica de Avelar Figueiredo Mafra Magalhães5.   

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Year:  2020        PMID: 33206881      PMCID: PMC7670748          DOI: 10.1590/0037-8682-0228-2020

Source DB:  PubMed          Journal:  Rev Soc Bras Med Trop        ISSN: 0037-8682            Impact factor:   1.581


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Dear Editor: Leprosy is an infectious disease caused by Mycobacterium leprae that affects the skin and peripheral nerves and may result in physical disabilities and/or deformities , which are associated with functional limitation, social isolation, stigma, and low quality of life . Although the burden of leprosy has reduced in recent decades, in 2017, more than 210,000 new cases have been reported in 150 countries, resulting in a global detection coefficient of 2.77/100,000 population . In Brazil, more than 28,000 cases are registered annually . Because it is considered a disease affecting low-income populations, the process of leprosy disease is potentially determined by the social context of the individuals , . For this purpose, the Social Needs Index can be used . The objective of our study was to analyze the temporal trends in the detection rate of new leprosy cases in the general population according to the stratum of the municipal Social Needs Index (SNI) in Bahia, Brazil, from 2001 to 2015. This was an ecological study involving all new cases of leprosy diagnosed in residents in Bahia, Brazil, from 2001 to 2015. The investigation process occurred in three stages: Step 1 - Calculation of the detection coefficient of new leprosy cases in the general population, based on the number of cases obtained from the National Information System for Notifiable Diseases (SINAN, in Portuguese) and population data from the Brazilian Institute of Geography and Statistics (IBGE). Crude and smoothed indicators were calculated by the local empirical Bayesian model. The smoothing was needed to reduce random fluctuation of the data. Step 2 - Obtaining the Social Needs Index (SNI): The SNI was elaborated according to the methodology proposed by UNICEF . The SNI involved four variables: 1) Economic and Social Performance-Economy and Finance Index (IPESE-EF), (2) average monthly value of per capita income (RENDAPERCAPIT), (3) proportion of extremely poor (%EXTRPOBRES), and (4) number of households with density larger than three persons per room (DOM3PPDOR). These variables were selected from previous studies in which these indicators were associated with the dynamics of leprosy transmission in Bahia state , . After the calculation, the municipalities were classified into quartiles: low SNI (0.142 to 0.259), medium SNI (0.260 to 0.369), high SNI (0.370 to 0.479), and very high SNI (0.480 to 0.699). Step 3 - For the trend analysis, we used the Joinpoint regression model . Trends were classified as increasing, decreasing, or stable. The annual percentage change (APC) was also obtained, considering a 95% confidence interval (95% CI) and significance level of 5%. The project was approved by the Human Research Ethics Committee of the Federal University of Alagoas: Protocol No. 2.212.723, of August 10, 2017. Between 2001 and 2015, 42,227 new leprosy cases were registered in Bahia state. The detection coefficient of new cases was 26.61/100,000 population in 2001, and it declined to 14.7/100,000 population in 2016, classifying Bahia state as highly endemic (between 10.0 and 19.9 new cases/100,000 population). A total of 252 (27.31%) municipalities were classified as very high SNI. The low and medium SNI showed a decreasing trend of the detection coefficient between 2005 and 2004, being high in the group with low SNI (APC -9.2% for the crude rate and APC -8.2% for the smoothed rate). Considering the time series (2001-2015), only the low SNI group showed a significantly decreasing trend (APC -2.9% for the crude rate and APC -2.6% for the smoothed) (Table 1).
TABLE 1:

Trend of detection coefficients of new leprosy cases in the general population, according to the Social Needs Index (SNI) stratum in Bahia state, Northeast Brazil, 2001-2015.

Social Needs stratumMunicipalities n (%)PeriodAPC (95% CI)P-valueTrend
Coefficient of detection of new leprosy cases - Crude indicator
Low12 (2.88)2001-200514.8 (4.2 to 26.5)<0.001Increasing
2005-2015-9.2 (-11.4 to -7.0)<0.001Decreasing
2001-2015-2.9 (5.7 to -0.1)<0.001Decreasing
Medium39 (9.35)2001-200415.0 (-7.8 to 43.3)0.25Stable
2004-2015-4.6 (-7.4 to -1.7)<0.001Decreasing
2001-2015-0.7 (-5.2 to 4.0)0.88Stable
High114 (27.34)2001-200615.3 (7.1 to 24.1)<0.001Increasing
2006-2019-17.0 (-40.4 to 15.4)0.21Stable
2009-2015-0.5 (-5.9 to 15.4)0.90Stable
2001-20150.9 (-5.5 to 7.7)0.81Stable
Very high252 (27.31)2001-200335.5 (-11.5 to 107.4)0.11Stable
2003-2015-4.9 (-7.3 to 2.5)0.43Stable
2001-20150.0 (-5.5 to 5.9)1.0Stable
Coefficient of detection of new leprosy cases - Smoothed indicator
Low12 (2.88)2004-200420.9 (6.3 to 37.5)<0.001Increasing
2004-2015-8.2 (-9.7 to -6.5)<0.001Decreasing
2001-2015-2.6 (-5.2 to -0.1)<0.001Decreasing
Medium39 (9.35)2001-201413.3 (-4.1 to 33.8)0.13Stable
2004-2015-4.3 (-6.4 to -2.1)<0.001Decreasing
2001-2015-0.8 (-4.2 to 2.8)0.77Stable
High114 (27.34)2001-200513.5 (2.5 to 25.7)<0.001Decreasing
2005-2015-5.6 (-8.0 to -3.2)<0.001Decreasing
2001-2015-0.5 (-3.5 to 2.5)0.71Stable
Very high252 (27.31)2001-200418.7 (-2.0 to 43.8)0.13Stable
2004-2015-5,2 (-7,6 to 2.7)0.32Stable
2001-2015-0.5 (-4.4 to 3.6)0.80Stable

Legends: APC, Annual Percent Change.

Legends: APC, Annual Percent Change. Several investigations have shown that the risk of leprosy is high among people living in poor living conditions , , , . Income inequality, social vulnerability, poverty, poor housing conditions, poor diet, and low educational level are considered social determinants related to disease transmission , , , . However, poor conditions may inhibit the early diagnosis, thus increasing the hidden prevalence, which justifies the low coefficients observed in the strata of higher SNI. General social improvements may be able to promote a reduction in the burden of leprosy. Investigations on the effects of policies on the magnitude of leprosy, for example, showed that municipalities with the largest coverage of Bolsa Família had the largest reductions in disease detection coefficients . Such public policies have also reached the most vulnerable municipalities, and this may justify the reduction in the rate of leprosy detection in the medium and high social vulnerability strata, as observed in this study. Finally, we recommend that in endemic areas, reducing social deprivation may result in disruption of the disease transmission chain and subsequent decline in the coefficient.
  7 in total

1.  Permutation tests for joinpoint regression with applications to cancer rates.

Authors:  H J Kim; M P Fay; E J Feuer; D N Midthune
Journal:  Stat Med       Date:  2000-02-15       Impact factor: 2.373

2.  Spatial modeling of leprosy in the state of Bahia and its social determinants: a study of health inequities.

Authors:  Carlos Dornels Freire de Souza; Carlos Feitosa Luna; Mônica de Avelar Figueiredo Mafra Magalhães
Journal:  An Bras Dermatol       Date:  2019-05-09       Impact factor: 1.896

3.  [Spatial modeling of leprosy in the state of Bahia, Brazil, (2001-2015) and social determinants of health].

Authors:  Carlos Dornels Freire de Souza; Roberto de Andrade Medronho; Franklin Gerônimo Bispo Santos; Mônica de Avelar Figueiredo Mafra Magalhães; Carlos Feitosa Luna
Journal:  Cien Saude Colet       Date:  2020-08-05

4.  Effect of the Brazilian conditional cash transfer and primary health care programs on the new case detection rate of leprosy.

Authors:  Joilda Silva Nery; Susan Martins Pereira; Davide Rasella; Maria Lúcia Fernandes Penna; Rosana Aquino; Laura Cunha Rodrigues; Mauricio Lima Barreto; Gerson Oliveira Penna
Journal:  PLoS Negl Trop Dis       Date:  2014-11-20

Review 5.  Leprosy: current situation, clinical and laboratory aspects, treatment history and perspective of the uniform multidrug therapy for all patients.

Authors:  Rossilene Conceição da Silva Cruz; Samira Bührer-Sékula; Maria Lúcia F Penna; Gerson Oliveira Penna; Sinésio Talhari
Journal:  An Bras Dermatol       Date:  2017 Nov-Dec       Impact factor: 1.896

Review 6.  Socioeconomic risk markers of leprosy in high-burden countries: A systematic review and meta-analysis.

Authors:  Julia Moreira Pescarini; Agostino Strina; Joilda Silva Nery; Lacita Menezes Skalinski; Kaio Vinicius Freitas de Andrade; Maria Lucia F Penna; Elizabeth B Brickley; Laura C Rodrigues; Mauricio Lima Barreto; Gerson Oliveira Penna
Journal:  PLoS Negl Trop Dis       Date:  2018-07-09

7.  Socioeconomic determinants of leprosy new case detection in the 100 Million Brazilian Cohort: a population-based linkage study.

Authors:  Joilda Silva Nery; Anna Ramond; Julia Moreira Pescarini; André Alves; Agostino Strina; Maria Yury Ichihara; Maria Lucia Fernandes Penna; Liam Smeeth; Laura C Rodrigues; Mauricio L Barreto; Elizabeth B Brickley; Gerson Oliveira Penna
Journal:  Lancet Glob Health       Date:  2019-07-19       Impact factor: 26.763

  7 in total

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