1 Projecto de Saúde de Bandim, Danish Epidemiology Science Centre, Bissau, Guinea-Bissau
2 Department of Infectious Diseases, Malmö University Hospital, Sweden
3 Hospital Raoul Follereau, Bissau, Guinea-Bissau
4 Laboratório Nacional de Saúde Pública, Bissau, Guinea Bissau
5 IMEA and INSERM U88, Paris and St-Maurice, France
6 Swedish Institute for Infectious Disease Control, Stockholm, Sweden
7 Department of Public Health and Clinical Medicine, University of Umeå, Sweden
Correspondence: Dr Per Gustafson, Department of Infectious Diseases, Malmö University Hospital, SE-205 02 Malmö, Sweden. E-mail: per.gustafson{at}inf.mas.lu.se
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Abstract |
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Methods In a prospective community study in Bissau, the capital of Guinea-Bissau, we assessed the impact of demographic, socioeconomic and cultural risk factors on active TB. A surveillance system in four districts of the capital identified 247 adult (15 years) cases of intrathoracic TB between May 1996 and June 1998. Risk factors were evaluated comparing cases with the 25 189 adults living in the area in May 1997.
Results The incidence of intrathoracic TB in the adult population was 471 per 100 000 person-years. Significant risk factors in a multivariate analysis were increasing age (P < 0.0001), male sex (odds ratio [OR] = 2.58, 95% CI: 1.85, 3.60), ethnic group other than the largest group (Pepel) (OR = 1.64, 95% CI: 1.20, 2.22), adult crowding (OR = 1.68, 95% CI: 1.18, 2.39 for >2 adults in household), and poor quality of housing (OR = 1.66, 95% CI: 1.24, 2.22). Household type was important; adults living alone or with adults of their own sex only, had a higher risk of developing TB than households with husband and wife present, the adjusted OR being 1.76 (95% CI: 1.11, 2.78) for male households and 3.80 (95% CI: 1.69, 8.56) for female households. In a multivariate analysis excluding household type, child crowding was a protective factor, the OR being 0.68 (95% CI: 0.51, 0.90) for households with >2 children per household.
Conclusions Bissau has a very high incidence of intrathoracic TB. Human immunodeficiency virus (HIV), increasing age, male sex, ethnicity, adult crowding, family structure, and poor housing conditions were independent risk factors for TB. Apart from HIV prevention, TB control programmes need to emphasize risk factors such as socioeconomic inequality, ethnic differences, crowding, and gender.
Accepted 28 August 2003
The human immunodeficiency virus (HIV) epidemic has aggravated an already severe tuberculosis (TB) situation leading to accelerating incidence figures worldwide.1 The WHO reports an 81% increase in notification rates for the African continent, from 58/100 000 in 1980 to 105/100 000 in 1999.2 In order to control TB in this situation it is crucial to fully understand the disease patterns. Surprisingly few community studies have been performed in developing countries to clarify how different factors interact in the development of active TB.3 The recent resurgence of interest in TB has mainly lead to an increase in studies of HIV and TB. Furthermore, studies from developing countries have in several cases failed to find support for risk factors like age, socioeconomic conditions, and crowding which were thought to have played major roles during the TB epidemic in the industrialized countries.4,5 For example, studies from South Africa6 and Malawi7 have found no association between crowding, socioeconomic conditions, and TB.
Guinea-Bissau, a small country on the west African coast, is one of the poorest countries in the world with a high prevalence of HIV type 2 (HIV-2) infection (6.8% in 1996),8 an increasing prevalence of HIV-1 (0% in 1987 to 2.2% in 1996 in the capital),8 and an increasing national incidence of TB (76/100 000 in 1987 to 153/100 000 in 1996).9 Previous studies from Bissau have shown high prevalences of HIV among TB patients, 38.8% of patients being HIV-positive.10 In 1996, we implemented a TB surveillance system, with passive and active case finding, in four suburban areas of the capital city, Bissau. The population in the areas has been followed demographically through a census system for many years.11 The demographic, socioeconomic, and environmental background data allowed us to study risk factors for active TB both at a community and household level. We did not evaluate behavioural factors in the present study.
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Materials and Methods |
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Criteria for inclusion in the study was age 15 years and one or more of the following symptoms and signs without other explanatory disease; cough for more than one month without improvement after antibiotic treatment, fever constantly or periodically for more than one month, weight loss, dyspnoea, haemoptysis, nightly sweats, or lymphadenopathy. Patients were examined clinically, interviewed using standardized questionnaires, and direct microscopy of morning sputum was done on 3 consecutive days as well as sputum culture and tuberculin skin test (using Multitest®, Bio-Merieux, France). Frontal chest x-rays were performed and pathological findings in the chest, including pulmonary changes, pleuritis, and hilar lymph node enlargements, were regarded as intrathoracic manifestations. Blood was drawn for HIV testing. Suspected cases with one or more sputum smears positive at direct microscopy or positive in culture for Mycobacterium tuberculosis were regarded as tuberculosis. As recommended by the International Union Against Tuberculosis and Lung Disease,13 patients with clinical signs, symptoms, and X-ray changes compatible with active intrathoracic TB, but without positive bacteriological tests, were treated with antibiotics (co-trimoxazole or amoxicillin) and then re-evaluated clinically and with chest X-ray. If there was no improvement and suspicion remained, the patient was diagnosed as having presumed tuberculosis. Smear positive patients and patients with severe disease were offered hospitalization if beds were available. Seven people were diagnosed and treated for active intrathoracic TB twice during the period; only the first episode was included in the analyses.
To evaluate the completeness of the TB surveillance system, we identified all adults who had died in the area during the study period. Two Guinean physicians performed verbal autopsies for 511 adults and all participating physicians later reviewed the forms in order to decide whether the individual was likely to have died with TB. Among the 511 deceased adults there were 39 who had died with symptoms of active TB. Two of these 39 had not been detected by the TB surveillance system and had thus not been included in the study. The two potential cases were not included in the analyses of incidence and risk factors for TB.
Many people living in the interior of Guinea-Bissau come to the capital and stay temporarily with relatives or friends to use the health services that the city offers. Such guests are not included in the demographic census files and these individuals were excluded from the analyses in the present paper.
Households and houses
A household was defined as one or several people living together recognizing a specific person as the head of household. For the risk factor analyses the households were classified in the following way: Type 1Adult men (one or more) only; Type 2Adult women (one or more) only; Type 3A male head of household with at least one wife present and possibly children; Type 4A male head of household without wife but with children or adult female(s) present; Type 5A female head of household without husband but with children or adult male(s) in the household.
Houses in the study area are one-storey, individually built, rectangular constructions, usually with 48 rooms and are inhabited by 24 families (households). The majority of houses do not have an internal ceiling, leaving a gap between the walls and the roof, letting air flow between the households, thereby potentially permitting transmission of air-borne and vector-borne infections between members of different households. Walls and house foundations are made of dried mud-cement bricks or plain mud/earth. The floors are covered with cement, tiles, or dried mud. Internal walls are plastered with cement or mud. Roofs are covered with straw or corrugated iron. Some houses have an indoor kitchen and toilet, however most houses have latrines outside and preparation of food is performed on the veranda. We used information on the construction and quality of houses as an indicator of socioeconomic status. The following factors related to housing quality were used as indicators of poor living condition: no indoor bathroom, no indoor kitchen, mud floor instead of cement/tiles, straw roof instead of corrugated iron, poor quality of roof, poor quality of walls, house foundation made of mud/earth instead of bricks/cement, poor quality of foundation of house, and plastering of walls with mud instead of cement.
Treatment
A 4-month intensive phase of daily directly observed treatment with Ethambutol, Isoniazid (INH), Rifampicin, and Pyrazinamide was followed by a 4-month continuation phase with Isoniazid and Ethambutol collected at the health centre twice per month by the patient. This treatment regimen was recommended for HIV-infected individuals by the national TB programme in Guinea-Bissau when the research project was initiated in 1996. For reasons of confidentiality and comparability HIV-infected and uninfected individuals received the same treatment. In addition, all patients were given vitamin B complex and multivitamins daily. Adherence to treatment was verified by pill count by the nurses supplying medication and an INH urine test was performed at the hospital at 2, 5, and 8 months of follow-up. Defaulting patients were visited by the nurse and encouraged to continue treatment. Specific HIV drugs or prophylactic treatment for HIV-related diseases were not available in Guinea-Bissau.
Laboratory methods
A field assistant collected morning sputum samples during 3 consecutive days. The sputum samples were investigated by direct microscopy for presence of acid-fast bacilli and the most representative sample was cultured. No isolate was resistant to two or more drugs. Sera were screened for HIV at the National Health Laboratory of Guinea-Bissau (LNSP). Laboratory methods have previously been described more extensively.10,12
Statistical analyses
The census data as well as information from questionnaires and results of laboratory analyses were entered in databases using dBASE V software. Incidence and risk factors were estimated comparing cases included between 6 May 1996, and 6 June 1998, with the adult population (15 years) living in the area on 6 May 1997. Annual incidence figures were calculated based on the 25 months of surveillance and using the adult population (
15 years) living in the area on 6 May 1997 as the mid-point or average population. Incidence figures are presented per 100 000. Test for trend was done using the extended Mantel-Haenszel
2-test in Epi Info version 6.04.
Estimation of odds ratios (OR) for risk factors was calculated in logistic regression models using SAS for Windows version 8.2. Apart from the nine housing quality factors mentioned above, the following risk factors were evaluated in univariate analyses: sex, age group, ethnic group, residential area, family structure, adult (15 years) crowding, child crowding, and presence of a ceiling in the house. All factors, except housing quality factors not significant on a 5% level, were then fitted into a multivariate model.
A multivariate analysis was performed comparing TB cases positive in direct microscopy or culture with the adult population. Since risk factors for TB and HIV may not be independent, a multivariate analysis comparing HIV-negative TB cases with the adult population was performed. Furthermore, a similar sub-analysis was performed comparing HIV-positive TB cases with the adult population. Note that the comparison of HIV-positive TB cases with the population may express the risk factors for HIV infection rather than risk factors for TB. Factors significant to a 5% level in the multivariate analysis comparing all cases with the adult population were included in these three sub-analyses.
Ethics
Pre- and post-test counselling regarding both HIV infection and TB were available. The patients were informed in writing in Portuguese and verbally in the common language, Creol, before being enrolled in the study. The study was approved by the Ministry of Public Health in Guinea-Bissau, and by the Central Ethical Committee of Denmark.
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Results |
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Male sex and increasing age were significant risk factors for TB in both univariate and multivariate analyses. The largest ethnic group Pepel had considerably lower risk of TB compared with the other groups. In the multivariate analysis for HIV-negative cases, the Pepel ethnic group, which constitutes around 40% of the population in the study area, had significantly lower incidence compared with the other groups (OR = 0.64, 95% CI: 0.44, 0.94). The TB incidence did not differ between the districts in the study area. The number of households per house or the number of people, adults or children, living in the same house had no effect on the incidence of TB (not in Table). The presence of a ceiling had no impact on TB. All of the housing factors used as indicators of poor living conditions increased the risk of TB (Table 2). In the multivariate model, quality of house foundations remained significant.
In the multivariate analyses, adults living in a household with husband and wife present had the lowest risk of developing TB. The increased risk was most apparent in households with only male (household type 1) or female (household type 2) adults and no children. This was true also when restricting the analysis to HIV-negative cases. Crowding was calculated separately as child crowding and adult crowding (>2 children and >2 adults per household, respectively). Adult crowding was a risk factor for TB; in an analysis including all variables, each adult in the household increased the risk of TB by 5% (95% CI: 0, 10%) (Table 3). The household type classification essentially depicted a difference between households with and without children. If household type was not included in the multivariate model maintaining the other variables as in Table 2, increasing number of children decreased the risk for TB (Table 4), the OR being 0.68 (95% CI: 0.51, 0.90) for households with >2 children per household.
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Discussion |
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Apart from the resident patients presented in this paper, the surveillance system detected 118 TB cases that came from the countryside and temporarily lived in the area when being diagnosed. These patients, even though they are not included in the incidence figures, may play an important role for the TB transmission in the urban area by adding to the infectious burden in the households they visit.
The TB surveillance system was initiated at the same time in 1996 and functioned in the same way in the four districts included in the present study. However, the areas have been followed for variable lengths of time, Mindara being included most recently in the demographic surveillance system. This could be the reason why Mindara had slightly higher incidence than the three other areas followed since the early 1980s (Table 2). Although the census has been periodically updated in all areas, an old census system may contain more relatives who are not really living in the area most of the time but maintain a second residence elsewhere. The result would be that the incidence was slightly underestimated because of too many people on the census list in the areas followed for 1520 years. The slightly higher incidence recorded in Mindara may have been more accurate.
The inclusion of all suspected TB cases could be questioned on the basis of diagnostic quality and it is possible that we have over-diagnosed active intrathoracic TB. However, it should be noted that cases, were diagnosed and treated against active TB, and incidence figures thus reflect the incidence of diagnosed and treated intrathoracic TB. Also when restricting the incidence figures to smear-positive cases only, the incidence is among the highest in the world.2 Almost 40% of our cases were HIV-positive, which is a group well-known to be smear-negative.15 It should be noted that our approach has not led us to overestimate the effects of the risk factors. Misclassification of cases would bias the OR towards 1.0 rather than produce false risk factors.
It is noteworthy that the TB incidence rates showed a significant increase with age, for both men and women (Table 1), also in the oldest age groups. Official WHO figures2 only report age-stratified notification rates for smear-positive cases, showing a decrease in incidence in the oldest age groups for Africa. Our results are consistent with this pattern; the incidence of smear-positive cases decrease in patients >55 years (Table 1). This discrepancy between all and smear-positive cases may be due to a tendency towards increased frequency of smear-negativity with old age.15 For the HIV-negative individuals there was a stable TB incidence up to age 44 and thereafter a marked increase. Our incidence rates, increasing with age, would correspond with data from the industrialized areas of Europe in the beginning of the 20th century.5,16
TB is associated with poverty. TB is more common in poorer countries2,14 but also within the individual countries, poorer living areas have been associated with TB in both industrialized countries4,17 and developing countries.18,19 Two studies from sub-Saharan Africa, however, failed to show an association between low socioeconomic level and active TB in adults.7,20 In the present study, we did not have the possibility of using income as a poverty factor and were restricted to secondary indicators for housing quality, but poor living conditions was an independent risk factor for active TB (Table 2). In our study we found indications that the ethnic group Pepel was less susceptible to TB, even when adjusting for socioeconomic background factors (Table 2).
Recently, gender issues and TB control have generated much interest. In most countries notification rates are higher for men than for women,2 even in countries where equal access to health care for men and women is likely.2 Hence, it has been debated whether the difference is due to behavioural, socioeconomic, or true biological effects, or a combination thereof,21 or due to TB being under-diagnosed or under-reported in women.22 In our study, we found that male sex was an important independent risk factor for TB (adjusted OR = 2.58, 95% CI: 1.85, 3.60), for all categories of patients (Table 2). The active case finding among contacts with TB cases and verbal autopsies should have minimized the problem of under-diagnosis for women. Furthermore, if males had been over-diagnosed this would have been most pronounced among cases diagnosed on clinical grounds. However, the malefemale ratio in those diagnosed on clinical grounds (61/29 = 2.1) differed little from the ratio among patients with confirmed TB (86/46 = 1.9). Hence, it is highly unlikely that under-diagnosis in women or over-diagnosis in men can explain the observed sex difference in incidence.
Though the literature is conflicting on the role of crowding, our study does suggest that adult crowding is a risk factor for TB. Adult crowding was a significant independent risk factor also for HIV-positive individuals, which may be an indication that exogenous infection, as opposed to re-activation of disease, may be a contributor to active TB in these people. Children are less likely to be infectious23 and child crowding in the household should therefore have limited effect. The lack of adjustment for family structure and separation of crowding into adults and children may be reasons that other studies have failed to show crowding to be a risk factor.
An interesting finding in the present analysis was that family structure seemed to play a role. Previous studies have shown that marital status affects the risk of TB, with single men having a greater risk of TB than married men.24 In the present study we found that people living without children, alone or with adults of their own sex only, have higher risks of developing TB than people living in households with children or/and adults of the opposite sex. This finding remained significant for all categories of TB cases (Table 2). Restricting the analysis to adults living in families without children, adults in type 1 and 2 households had increased rates compared with household type 3, the adjusted OR being 1.60 (95% CI: 0.69, 3.73) and 4.98 (95% CI: 1.01, 24.8), respectively. The increased risk of adults living without children or individuals of the opposite sex may have to do with differences in lifestyles, but could possibly also be a result of some protection from contact with children since our analysis suggested that the protective effect increased with the number of children. Some protection from contact with children, possibly through immune stimulation from exposure to childhood infections, could be one of the reasons for the high TB incidence among young adults and old people, neither of whom would have much contact with young children. Since there was no difference in incidence for adult men and women living alone or with adults of their own sex, closer contact with children might also be one of the reasons that women have less TB than men.
Our census system did not contain complete information on smoking habits, alcohol abuse, nutritional status, schooling, presence of animals in the house, and working conditions. These factors, together with genetic differences or concomitant diseases in the individual, may play important roles in the development of TB and may explain some of our findings, such as the higher risk in certain ethnic groups, members of certain household types, and males. The interactions between such factors and the risk factors presented in this paper need further investigation.
TB research in the last decades has focused on co-infection with HIV. The present study represents one of very few community studies of non-HIV risk factors for active TB among adults in a sub-Saharan setting. We have shown that the risk factors for active TB in developing countries today are the same that physicians encountered in their daily work 100 years ago in Europe and North America. Age, sex, ethnic group, adult crowding, poverty, and family structure are still highly important factors for active TB even in the era of the HIV epidemic. It is of great importance that international organizations, as well as national TB control programmes, acknowledge that there are differences in impact of risk factors in different settings and measures to combat TB may need to be targeted for the specific populations. Poverty reduction is essential and governments need to adopt action plans in order to reduce the absolute poverty and crowding among the most vulnerable. Recognizing that there may be major ethnic differences in the incidence of TB might help to define important behavioural risk factors and to target interventions to those most in need. It would seem essential to explore why mothers have less TB. Integration of TB and HIV control programmes may be beneficial in terms of counselling, education, and reducing the stigmatization of both diseases, as well as for specific issues such as TB case finding and prophylactic TB treatment for HIV positives.
KEY MESSAGES
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Acknowledgments |
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This study would not have been possible without the dedicated work of the field assistants, laboratory technicians, nurses and physicians working daily with the problems concerning tuberculosis. Special thanks go to Mali Jalo.
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References |
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2 World Health Organization. Global Tuberculosis Control. Geneva, Switzerland: WHO, 2001. WHO/CDS/TB/2001.287.
3 Lienhardt C. From exposure to disease: The role of environmental factors in susceptibility to and development of tuberculosis. Epidemiol Rev 2001;23:288301.[ISI][Medline]
4 Stein L. Tuberculosis and the social complex in Glasgow. Brit J Soc Med 1952;6:148.
5 Groth-Petersen E, Knudsen J, Wilbek E. Epidemiological basis of tuberculosis eradication in an advanced country. Bull World Health Org 1959;21:549.
6 Coetzee N, Yach D, Joubert G. Crowding and alcohol abuse as risk factors for tuberculosis in the Mamre population. Results of a case-control study. S Afr Med J 1988;74:35254.[ISI][Medline]
7 Glynn JR, Warndorff DK, Malema SS et al. Tuberculosis: associations with HIV and socioeconomic status in rural Malawi. Trans R Soc Trop Med Hyg 2000;94:50003.[ISI][Medline]
8 Larsen O, da Silva Z, Sandstrom A et al. Declining HIV-2 prevalence and incidence among men in a community study from Guinea-Bissau. AIDS 1998;12:170714.[CrossRef][ISI][Medline]
9 Ministério da Saúde PúblicaRepública da Guiné-Bissau. Programa Nacional de Luta contra a Lepra e TuberculoseRelatório 1996. 2031997.
10 Seng R, Gustafson P, Gomes VF, Vieira CS, Rabna P, Samb B. Community study of the relative impact of HIV-1 and HIV-2 on intrathoracic tuberculosis. AIDS 2002;16:105966.[CrossRef][ISI][Medline]
11 Aaby P. Bandim: an unplanned longitudinal study. In: Das Gupta M, Aaby P, Pison G, Garenne M, (eds). Prospective Community Studies in Developing Countries. Oxford: Clarendon, 1997, pp. 27696.
12 Gustafson P, Gomes VF, Vieira CS et al. Tuberculosis mortality during a civil war in Guinea-Bissau. JAMA 2001;286:599603.
13 Enarson DA, Rieder HL, Arnadottir T, Trébucq A. Management of Tuberculosis. A Guide for Low Income Countries. 5th Edn. Paris: International Union Against Tuberculosis and Lung Disease, 2000.
14 Dye C, Scheele S, Dolin P, Pathania V, Raviglione MC. Consensus statement. Global burden of tuberculosis: estimated incidence, prevalence, and mortality by country. WHO Global Surveillance and Monitoring Project. JAMA 1999;282:67786.
15 Samb B, Sow PS, Kony S et al. Risk factors for negative sputum acid-fast bacilli smears in pulmonary tuberculosis: results from Dakar, Senegal, a city with low HIV seroprevalence. Int J Tuberc Lung Dis 1999;3:33036.[ISI][Medline]
16 Tuberculosis statistics. Tubercle 1930;Sept.:54142.
17 Hawker JI, Bakhshi SS, Ali S, Farrington CP. Ecological analysis of ethnic differences in relation between tuberculosis and poverty. BMJ 1999;319:103134.
18 van Rie A, Beyers N, Gie RP, Kunneke M, Zietsman L, Donald PR. Childhood tuberculosis in an urban population in South Africa: burden and risk factor. Arch Dis Child 1999;80:43337.
19 Mukadi YD, Wiktor SZ, Coulibaly IM et al. Impact of HIV infection on the development, clinical presentation, and outcome of tuberculosis among children in Abidjan, Cote d'Ivoire. AIDS 1997;11:115158.[CrossRef][ISI][Medline]
20 Schoeman JH, Westaway MS, Neethling A. The relationship between socioeconomic factors and pulmonary tuberculosis. Int J Epidemiol 1991;20:43540.[Abstract]
21 Diwan W, Thorson A, Winkvist A (eds). Gender and Tuberculosis. NHV Report 1998. Göteborg: Nordic School of Public Health, 1998.
22 Holmes CB, Hausler H, Nunn P. A review of sex differences in the epidemiology of tuberculosis. Int J Tuberc Lung Dis 1998;2:96104.[ISI][Medline]
23 Crofton J, Horne N, Miller F. Clinical Tuberculosis. London: The Macmillan Press Ltd, 1992.
24 Christensen O, Bjartveit K, Dahlstrom G. Tuberculosis situation in the Scandinavian countries. Scand J Respir Dis Suppl 1978;102:1940.[Medline]