Higher loss of livelihood and impoverishment in households affected by tuberculosis compared to non-tuberculosis affected households in Zimbabwe: A cross-sectional study.
Collins TimireRein M G J HoubenDebora PedrazzoliRashida Abbas FerrandClaire J CalderwoodVirginia BondFredrick MbibaKatharina KranzerPublished in: PLOS global public health (2024)
Tuberculosis (TB) disproportionally affects poor people, leading to income and non-income losses. Measures of socioeconomic impact of TB, e.g. impoverishment and patient costs are inadequate to capture non-income losses. We applied impoverishment and a multidimensional measure on TB and non-TB affected households in Zimbabwe. We conducted a cross-sectional study in 270 households: 90 non-TB; 90 drug-susceptible TB (DS-TB), 90 drug-resistant TB (DR-TB) during the COVID-19 pandemic (2020-2021). Household data included ownership of assets, number of household members, income and indicators on five capital assets: financial, human, social, natural and physical. Households with incomes per capita below US$1.90/day were considered impoverished. We used principal component analysis on five capital asset indicators to create a binary outcome variable indicating loss of livelihood. Log-binomial regression was used to determine associations between loss of livelihood and type of household. TB-affected households were more likely to report episodes of TB and household members requiring care than non-TB households. The proportions of impoverished households were 81% (non-TB), 88% (DS-TB) and 94% (DR-TB) by the time of interview. Overall, 56% (152/270) of households sold assets: 44% (40/90) non-TB, 58% (52/90) DS-TB and 67% (60/90) DR-TB. Children's education was affected in 33% (55/168) of TB-affected compared to 14% (12/88) non-TB households. Overall, 133 (50%) households experienced loss of livelihood, with TB-affected households almost twice as likely to experience loss of livelihood; adjusted prevalence ratio (aPR = 1.78 [95%CI:1.09-2.89]). The effect of TB on livelihood was most pronounced in poorest households (aPR = 2.61, [95%CI:1.47-4.61]). TB-affected households experienced greater socioeconomic losses compared to non-TB households. Multisectoral social protection is crucial to mitigate impacts of TB and other shocks, especially targeting poorest households.
Keyphrases
- mycobacterium tuberculosis
- drug resistant
- healthcare
- mental health
- pulmonary tuberculosis
- young adults
- drug delivery
- pseudomonas aeruginosa
- hepatitis c virus
- risk factors
- machine learning
- cystic fibrosis
- quality improvement
- human immunodeficiency virus
- case report
- artificial intelligence
- data analysis
- acinetobacter baumannii