Prevalence of non‐communicable diseases among household contacts of people with tuberculosis: A systematic review and individual participant data meta‐analysis

• Published in: Tropical medicine & international health 2024-09, Vol.29 (9), p.768-780
• Main Authors: Hamada, Yohhei, Quartagno, Matteo, Malik, Farihah, Ntshamane, Keolebogile, Tisler, Anna, Gaikwad, Sanjay, Acuna‐Villaorduna, Carlos, Bhavani, Perumal Kannabiran, Alisjahbana, Bachti, Ronacher, Katharina, Apriani, Lika, Becerra, Mercedes, Chu, Alexander L., Creswell, Jacob, Diaz, Gustavo, Ferro, Beatriz E., Galea, Jerome T., Grandjean, Louis, Grewal, Harleen M. S., Gupta, Amita, Jones‐López, Edward C., Kleynhans, Léanie, Lecca, Leonid, MacPherson, Peter, Murray, Megan, Marín, Diana, Restrepo, Blanca I., Shivakumar, Shri Vijay Bala Yogendra, Shu, Eileen, Sivakumaran, Dhanasekaran, Vo, Luan Nguyen Quang, Webb, Emily L., Copas, Andrew, Abubakar, Ibrahim, Rangaka, Molebogeng X.
• Format: Article
• Language: English
• Subjects: Age; chronic diseases; Comorbidity; Confidence intervals; Data analysis; Diabetes; Diabetes mellitus; Epidemiology; Estimates; Health risks; Households; Medical records; Medical screening; Meta-analysis; Risk factors; Risk sharing; Sex; Statistical analysis; Systematic review; Tuberculosis
• ISSN: 1360-2276; 1365-3156; 1365-3156
• DOI: 10.1111/tmi.14038

Objective To investigate the prevalence of non‐communicable diseases among household contacts of people with tuberculosis. Methods We conducted a systematic review and individual participant data meta‐analysis. We searched Medline, Embase and the Global Index Medicus from inception to 16 May 2023. We included studies that assessed for at least one non‐communicable disease among household contacts of people with clinical tuberculosis. We estimated the non‐communicable disease prevalence through mixed effects logistic regression for studies providing individual participant data, and compared it with estimates from aggregated data meta‐analyses. Furthermore, we compared age and sex‐standardised non‐communicable disease prevalence with national‐level estimates standardised for age and sex. Results We identified 39 eligible studies, of which 14 provided individual participant data (29,194 contacts). Of the remaining 25 studies, 18 studies reported aggregated data suitable for aggregated data meta‐analysis. In individual participant data analysis, the pooled prevalence of diabetes in studies that undertook biochemical testing was 8.8% (95% confidence interval [CI], 5.1%–14.9%, four studies). Age‐and sex‐standardised prevalence was higher in two studies (10.4% vs. 6.9% and 11.5% vs. 8.4%) than the corresponding national estimates and similar in two studies. Prevalence of diabetes mellitus based on self‐report or medical records was 3.4% (95% CI 2.6%–4.6%, 14 studies). Prevalence did not significantly differ compared to estimates from aggregated data meta‐analysis. There were limited data for other non‐communicable diseases. Conclusion The prevalence of diabetes mellitus among household contacts was high while that of known diabetes was substantially lower, suggesting the underdiagnosis. tuberculosis household contact investigation offers opportunities to deliver multifaceted interventions to identify tuberculosis infection and disease, screen for non‐communicable diseases and address shared risk factors.