KAP TB in Senior Management Officials of Companies With Increased Silica Exposure

Tuberculosis (TB) continues to pose a significant global health burden, particularly among individuals in the economically productive age group of 15-64 years. In Zambia, 85% of TB cases occur in this demographic, underscoring the dual public health and socio-economic impact. The risk is compounded in industries with high exposure to crystalline silica dust, such as mining, construction, drilling, cement, brick, tile, glass, and ceramics manufacturing. Prolonged inhalation of silica dust can lead to silicosis, a condition that increases the risk of TB three to four times compared to individuals without silicosis. Even without silicosis, silica exposure alone elevates TB risk. Poor workplace conditions, including overcrowding and inadequate ventilation, further exacerbate transmission risks.

Recognizing these occupational hazards, the study aimed to assess the knowledge, attitudes, and practices (KAP) of senior management officials in companies with high silica exposure. These officials play a critical role in shaping workplace policies and interventions, making their understanding and attitudes toward TB prevention and management essential for effective workplace health strategies.

The research was conducted as a descriptive cross-sectional study between February and October 2022 in Lusaka and Southern provinces of Zambia. These provinces were selected due to their concentration of industries associated with silica dust exposure. The study focused on senior management officials, defined as either the most senior staff in an organization or heads of divisions/departments, given their influence on workplace health policies.

The sample population was drawn from the Zambia Chamber of Commerce and Industry (ZACCI), an umbrella organization representing businesses across all sectors. ZACCI advocates for workplace legislation and a conducive business environment. Companies known to produce silica dust were identified under categories including mining, construction, cement manufacturing, brick and tile manufacturing, and glass and ceramic manufacturing. The sampling frame included 1 mining company, 73 construction companies, 1 cement company, 9 brick/tile companies, and 10 glass/ceramic companies.

Each company was asked to nominate at least one senior official to complete the questionnaire, with a maximum of two responses per company. This ensured representation across industries while maintaining focus on individuals with policy-making authority.

Data were collected using a multiple-choice electronic questionnaire developed in accordance with WHO guidelines for TB KAP surveys. The questionnaire was self-administered in English via Google Forms and contained 28 mandatory closed-ended questions:

• Knowledge: 7 questions
• Attitudes: 8 questions
• Practices: 13 questions (with 5 excluded from scoring as they were programmatic) Of the 28 questions, 21 were multiple-choice, while 7 required a single best answer. The questionnaire was distributed via email, with three reminders sent to encourage participation. Due to low response rates from email reminders, physical follow-ups were conducted. Ultimately, participants completed the survey independently on tablets between June and November 2022.

Responses were validated by three medical doctors. A response was considered correct if at least two doctors agreed. This ensured accuracy and minimized bias in scoring. Responses marked as "don't know," "not sure," or "other" were treated neutrally with a score of 0. Ambiguous "other" responses were excluded from analysis.

Survey responses were stored on Google Forms, downloaded into a CSV file, and imported into Python (version 3.8) for recoding. The dataset was then analyzed using STATA (version 18.5). Descriptive statistics were used to summarize participant characteristics and categorical variables.

A scoring system was applied:

• Knowledge: maximum of 17 points
• Attitudes: maximum of 7 points
• Practices: maximum of 14 points Correct responses scored 1, incorrect responses scored 0. Scores were categorized into "poor" or "good" based on mean or median cutoffs depending on distribution. Logistic regression was used to explore associations between participant characteristics (age, gender, industry, department) and KAP outcomes. Univariable analysis identified potential associations, followed by multivariable analysis to control for confounders. Variables with p-values above 0.05 were excluded unless only two variables remained significant, in which case the higher p-value variable was retained.