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Occupations with an increased prevalence of self-reported asthma in Indian adults

Objectives Occupational asthma remains relatively under-recognized in India with little or no information regarding preventable causes. We studied occupations with an increased prevalence of self-reported asthma among adult men and women in India. Methods Analysis is based on 64 725 men aged 15–54 years and 52 994 women aged 15–49 years who participated in India’s third National Family Health Survey, 2005–2006, and reported their current occupation. Prevalence odds ratios (ORs) for specific occupations and asthma were estimated using multivariate logistic regression, separately for men and women, adjusting for age, education, household wealth index, current tobacco smoking, cooking fuel use, rural/urban residence and access to healthcare. Results The prevalence of asthma among the working population was 1.9%. The highest odds ratios for asthma were found among men in the plant and machine operators and assemblers major occupation category (OR: 1.67; 95% CI: 1.14–2.45; p = 0.009). Men working in occupation subcategories of machine operators and assemblers (OR: 1.85; 95% CI: 1.24–2.76; p = 0.002) and mining, construction, manufacturing and transport (OR: 1.33; 95% CI: 1.00–1.77; p = 0.051) were at the highest risk of asthma. Reduced odds of asthma prevalence in men was observed among extraction and building trades workers (OR: 0.72; 95% CI: 0.53–0.97; p = 0.029). Among women none of the occupation categories or subcategories was found significant for asthma risk. Men and women employed in high-risk occupations were not at a higher risk of asthma when compared with those in low-risk occupations. Conclusions This large population-based, nationally representative cross-sectional study has confirmed findings from high income countries showing high prevalence of asthma in men in a number of occupational categories and subcategories; however, with no evidence of increased risks for women in the same occupations.


Introduction
Asthma is among the most common chronic diseases in working-aged populations. Among the general adult population in high income countries, it has been estimated that 2-5% of patients with asthma have occupational asthma [1,2]; some studies from the United States and Japan have estimated the risk to be as high as 15% [3]. Among populations at risk due to their exposure to known sensitizing agents, the risk of developing occupational asthma can be as high as 5-10% per year [1].
Recent studies of the global burden of disease over the last two decades indicate that occupational lung diseases such as chronic obstructive pulmonary disease (COPD), asthma and pneumoconioses caused by exposure to airborne particulates are major contributors to mortality and disability, particularly in low-and-middle income countries [3] with much of this burden falling on working age groups. However, occupational asthma remains under-studied and under-recognized in lowand middle-income countries where diagnosis and management are considered to be poor [3]. There have been no previous studies reporting occupational risk factors for asthma in India in a nationally representative population. Also, there is a particular lack of information on occupational risk factors for women workers [4]. Women's work has traditionally been considered safe and less hazardous to health in comparison with men's work [5]. This has resulted in a lack of information on occupational hazards for women workers [4], and our knowledge of occupational health has mainly been based on studies of men. Differences in occupational morbidity have also been observed for men and women with the same job title, suggesting that even in the same occupation, men and women are not equally exposed to particular risk factors for disease [6]. Very few studies in India have investigated the prevalence of occupational risk factors in women workers, or compared the distribution of risk factors between women and men. We therefore studied associations between occupation and self-reported asthma among adult men and women in India.

Study design and participants
India's third National Family Health Survey (NFHS-3, 2005(NFHS-3, -2006 was designed on the lines of the Demographic and Health Surveys (available at www.measuredhs.com) that have been conducted in many low-and middle-income countries since the 1980s. The NFHS has been conducted in India for three successive rounds, each at an interval of 5 years. NFHS-3 collected demographic, socioeconomic and health information from a nationally representative probability sample of 124 385 women aged 15-49 years and 74 369 men aged 15-54 years residing in 109 041 households. The sample is a multistage cluster sample with an overall response rate of 98%. All states of India are represented in the sample (except the small Union Territories), covering more than 99% of the country's population. Full details of the survey have been published elsewhere [7]. The analysis presented here focuses on 64 725 men aged 15-54 years and 52 994 women aged 15-49 years who reported their current occupation.

Outcome measure
The survey included several questions relating to the current health status of the respondents during the personal interview, including the question, ''Do you currently have asthma?''. The response options were ''yes'', ''no'' and ''don't know''. The survey was conducted using an interviewer-administered questionnaire in the native language of the respondent using a local, commonly understood term for asthma. A total of 18 languages were used with back translation to English to ensure accuracy and comparability. However, no physician diagnosis of asthma was obtained and it was not feasible to clinically test for the disease.

Occupational categories
In NFHS-3, information on respondent's current occupation was obtained through self-reports at the time of personal interview. Altogether, there were 98 categories of occupations reported. These occupations were then coded using the Revised Indian National Classification of Occupations [8]. NCO  The NCO is a hierarchical skills-based classification of occupation which consists of 10 divisions (one-digit code); 30 sub-divisions (two-digit code); 116 groups (three-digit code); 439 families (four-digit code) and 2945 occupations (six-digit code). Table 1 shows an example of different levels of classifications in NCO. The choice of the most applicable six-digit occupation code was based on the self-reported job title as well as the respondent's description of tasks. A broad list of occupational categories provided in the NFHS-3 data is provided in the Appendix with corresponding NCO codes.

Covariates
The socio-demographic factors considered in the present analysis included current smoking status (not smoking, smoking -data on former smoking is not available in the data); household cooking fuel use (clean fuel which include kerosene, liquefied petroleum gas/natural gas, biogas or electricity; solid fuel-less clean which include coal/lignite or charcoal; biomass fuel-not clean which include wood, straw/ shrubs/grass, agricultural crop waste, dung cakes, others); age (15-19, 20-34, 35-49 and 50-54 years); education (no education, primary, secondary and higher); wealth index (measured by an index based on household ownership of assets and graded as lowest, second, middle, fourth and highest) was computed using previously described methods [7]; place of residence (urban and rural); and access to health care (public medical sector, NGO or trust hospital/clinic, private medical sector and other sources). For a definition of variables, refer Table 2.

Statistical analyses
The analysis was conducted separately for women and men, because they may have different occupational exposures (even in the same job category), as well as different nonoccupational exposures [6]. From the analysis, we removed occupation category such as ''workers not classified by occupations'' (NCO 2004 Code 10; men n ¼ 9549; 12.8% and women n ¼ 71 343; 57.4%), since this include new workers seeking employment and currently not working. We first examined asthma prevalence by various occupational categories in bivariate analysis stratified by gender. Prevalence odds ratios (Ors) [9] and 95% confidence intervals (CIs) were 2222.10 Physicians, Ayurvedic estimated using multivariate logistic regression, adjusting for age, education, household wealth index, current tobacco smoking, household fuel use, rural/urban residence and access to healthcare. The selection of the high-risk groups was based on those groups that had consistently shown increased risks in previous studies in high income countries [10][11][12]. Selections of occupations were generally based on findings from population-based studies rather than studies of specific subgroups. Participants who reported currently working exclusively in professional, clerical or administrative jobs (referNCO codes in Appendix Table A1) were classified as having low-risk occupations and were considered the reference group in this study. Table A2 in Appendix gives the full sample distribution and asthma prevalence in respective single occupational categories stratified by gender. As certain states and certain categories of respondents were oversampled, in all analyses sample weights were used to restore the representativeness of the sample [7]. Before carrying out the multivariate model, we assessed the possibility of multicollinearity between the covariates. In the correlation matrix of covariates, all pair-wise Pearson correlation coefficients were 50.5, suggesting that multicollinearity is not a problem. All analyses including the logistic regression models were conducted using the SPSS statistical software package Version 19 (IBM SPSS Statistics, Chicago, IL).

Ethics approval
The NFHS-3 survey received ethical approval from the International Institute for Population Science's Ethical Review Board and the Indian government. Participation in the survey was totally voluntary. Prior informed written consent was obtained from each respondent. The analysis presented in this study is based on secondary analysis of existing survey data with all identifying information removed. Table 2 shows the characteristics of the study participants. The prevalence of current asthma was 1.9% both among men and women. Three-fifths men (62.9%) were currently smoking while only 2.3% women were current smokers. More than half of the respondent's (both men and women) were residing in households using biomass -not a clean fuel for cooking. Two out of five respondents were in age group 20-34 years and 1 in 5 men and 1 in 10 women belonged to households with highest wealth. A majority of the respondents lived in rural areas. More than half the women were not educated while almost half of men were with secondary education. A majority of the respondents have access to private medical sector health services.

Characteristics of the study participants
Asthma prevalence for major occupation categories by gender (adjusted odds ratios) Table 3 shows the prevalence odds ratios of asthma in major occupational categories separately for men and women. Of the 10 major NCO-2004 occupational categories, statistically significant elevated asthma risks in men was observed only among plant and machine operators and assemblers (OR: 1.67; 95% CI: 1.14-2.45; p ¼ 0.009). In women, the odds of self-reported asthma were not significantly higher in any major occupational category.
Asthma prevalence for major occupation subcategories by gender (adjusted odds ratios) Table 4 shows the prevalence odds ratios of asthma in various occupational subcategories separately for men and women. Of the major NCO-2004 occupation subcategories, statistically significant elevated odds of asthma in men were observed among machine operators and assemblers (OR: 1.85; 95% CI: 1.24-2.76; p ¼ 0.009), and among labourers in mining, construction, manufacturing and transport (OR: 1.33; 95% CI: 1.00-1.77; p ¼ 0.051). Reduced odds of asthma in men was observed among extraction and building trades workers (OR: 0.72; 95% CI: 0.53-0.97; p ¼ 0.029). In women, no occupation was found significant for asthma risk.
Asthma prevalence for high-risk occupations by gender (adjusted odds ratios) Table 5 shows the prevalence odds ratios of asthma for highrisk occupation separately for men and women. Both men and

Main findings
This study examined the prevalence of asthma in a range of occupational categories, subcategories and high-risk occupations as reported by the current working population in India. This population-based survey has shown increased risks of asthma among men in a number of occupation categories, such as plant and machine operators and assemblers, and subcategories, such as mining, construction, manufacturing and transport, machine operators and assemblers, but has found no risk for women in the same occupations. Both men and women working in high risk occupations were not at significantly higher risk of self-reported asthma when compared with low-risk occupations. Our study adds to the currently sparse evidence on occupations with an increased prevalence of self-reported asthma in Indian adults. Our study has confirmed findings from previous studies in high-income countries showing elevated risks in a number of occupation categories and subcategories [13,14] among men. The European Community Respiratory Health Survey (ECRHS) consistently found elevated risks of current asthma symptoms for farmers across the 12 participating countries with an overall risk of OR: 1.73 (95% CI: 1.00-3.01) [15]. The New Zealand component of the ECRHS reported an excess risk of asthma symptoms of OR: 1.95 (95% CI: 0.74-5.11) compared to the professional, administrative, clerical and service group [16]. There is limited evidence on the risk of asthma symptoms in sales workers around the globe. Examining the industry in addition to the occupation may provide some insight into the excess risks observed in this group. Although the evidence is sparse, other population based surveys have also identified excess asthma risks in the protective services industry [13] and in stock clerks [17]. The potential causative agents in the high risk occupational categories may be respiratory allergens and irritants [18] including sterilizers and disinfectants such as glutaraldehyde or bleach [12] in the case of nurses and health professionals; exposure to dust and oils and solvents in case of trade workers [6]; exposure to pesticides and acids or alkalis in the case of agriculture and fishery workers [6]; exposure to smoke/fume/ gas [19,20], working night shift and working irregular hours [21] in the case of plant and machine operators and assemblers [6,22]; lifting [23], exposure to loud noise [24], and the use of personal protective equipment in case of manual occupational groups [6,25].
Gender differences in occupational distribution, i.e. men and women working in different jobs and therefore being exposed to different risk factors, play an important role in many of these differential outcomes [26]. In the present analyses, we found no effect of occupation on asthma among women in India. This might be because, our analyses only assessed asthma prevalence in the current occupation and did not take into account duration or intensity of exposure (not available in the survey), which may also impact on gender differences in exposure and ultimately gender differences in occupational health. For example, female workers are more often employed part time and, therefore, more likely to experience shorter exposure duration [6].

Some differences compared with previous studies
Although many epidemiological studies in high risk workplaces have been conducted in high-income countries, studies in low-and middle-income countries are few with the exception in Africa where studies in occupational exposure of asthma have been conducted in South Africa [27], Morocco [28], Nigeria [29], Ethiopia [30] and Tanzania [31]. However, very few studies have been reported in other low-and middleincome countries. Two earlier studies in India reported of occupational asthma prevalence in specific occupations. An earlier study of two silk filatures (processing natural silk) in India reported a 17% prevalence of asthma due to silkworm allergens [32]. Another study which examined the long-term effects of metal dusts on the broncho-pulmonary system among 104 polishers and 90 unexposed controls reported that a prevalence of 4.8% of occupational asthma and 6.7% of chronic bronchitis, confined only to polishers. Workers in a cement factory in the United Arab Emirates had a two-fold higher prevalence of asthma compared to an unexposed group (6% versus 3%) [33]. Women performing indoor jobs in Iran had an 11% prevalence of asthma, which was more prevalent among those involved with bread baking, carpet weaving and poultry feeding activities [34]. A few small-scale studies among Chinese workers have reported a high prevalence (27%) of work-related wheeze and lung function impairment among workers at the furniture factory [35], food harvesting and processing industry [36] and fruit farms in Korea [37]. Certain occupational groups are known to be at particular high risk of occupational asthma, including laboratory workers, healthcare workers, construction workers, bakers, woodworkers handling western red cedar and chemical workers exposed to isocyanates [10]. However, many of these findings are from studies in specific industries, and only some have been investigated in epidemiological studies of the general population.

Strengths and weaknesses of the study
This study has several important strengths. Our study includes a large nationally representative study sample, which allows comparisons to be made between men and women and the ability to examine occupational asthma risk. The men and women covered by this survey were representative of the total working population, as opposed to similar studies that were limited to selected occupation or industry groups [38,39]. We could also quantify gender differences in asthma prevalence in occupational categories and subcategories at the population level and among men and women working in the same occupation. This is the first study that not only quantified the gender differences in occupational asthma at the population level, but also investigated whether any gender differences in occupational exposure exist for men and women working in the same occupation. However, it was not possible to investigate whether the observed gender differences in occupational asthma were entirely due to (a) the segregation of men and women into different occupations or could also be due to (b) men and women with the same occupation carrying out different tasks [6]. This study has other limitations. First, we found that the prevalence of self-reported asthma (both in general population and currently employed population) in this large, nationally representative survey was low compared to other Indian studies carried out clinically or in specific geographical locations [40][41][42][43] where the prevalence ranged from 1% to over 3%. Although several studies have been conducted in India on asthma prevalence in children and adolescents [44,45] but very few studies have been conducted in adults [46][47][48]. Due to the general challenges of measuring asthma in population-based studies [49], the measurement of asthma in the NFHS also has apparent limitations. The NFHS assessment of asthma prevalence was based on a single question, in contrast to a hierarchy of asthma/wheeze outcomes based on responses to standardized respiratory questionnaires. No effort was made in NFHS-3 to clinically test for asthma or to inquire whether the response was based on a physician's diagnosis. Given the marked variation in recognition and presentation to a physician by an individual with recurrent wheezing or asthma episodes, considerable differences in diagnostic labelling and treatment by doctors between populations [50] and suboptimal levels of access to health care, physician-diagnosed asthma prevalence or use of asthma medication is equally problematic in the Indian context [51]. Furthermore, neither asthma severity nor the frequency of asthma attacks was ascertained in NFHS-3. Overall, the NFHS data appear to under estimate asthma prevalence compared with other studies in India [42,43], including those from the International Study of Asthma and Allergies in Childhood (ISAAC) [52], although prevalence is similar to those of other countries in the subcontinent, such as Bangladesh and Nepal [53,54].
Other possible sources of bias should be considered when interpreting the findings of this study. First, asthma prevalence was based on self-reports of asthma itself rather than asthma symptoms, and respondents may have been more likely to report some disease conditions such as chronic bronchitis or chronic obstructive pulmonary disease with similar symptoms to asthma due to their lack of awareness, low educational status and hesitation to disclose diseases. However, rigorous efforts were employed in NFHS-3 to obtain reliable self-reported data [55]. The survey used local terminology and commonly understood terms to describe the disease, rigorously trained interviewers, supervisors and standard quality checks such as cross checks and back checks (refer Appendix for detail). It is also important to recognise here that self-report of asthma is not as accurate as clinical measures of asthma and there is a risk of underreporting of mild asthma in self-reporting as well. Further, a higher proportion of healthcare workers in the female reference population may explain why the association between occupation category and asthma was not significant in women.
We studied a large number of occupational groups and subgroups and it is therefore possible that some of our results may have been due to chance. Nevertheless, we obtained more significantly positive findings in some occupations than would have been expected by chance alone. Also, several of the occupational groups identified in our analyses have been consistently reported by other studies to be at high-risk of asthma, and the consistency of excess risks in certain occupations in this study independent of the disease definition (current asthma) used suggests that the findings are relatively robust. We also adjusted for other high-risk occupations in the analyses and this only had a small effect on the results. Furthermore, there are several potential problems with selecting a single reference group which includes: (i) weak statistical power to detect associations due to small numbers; (ii) issues of bias arising from comparing to an ''unexposed'' group who are likely to differ on a number of factors other than the one under study; and (iii) previous studies have acknowledged that the assumption of lack of exposure in the reference group is not entirely plausible [56].

Conclusions
This population-based nationally representative large scale cross-sectional study has confirmed the findings of highincome countries showing high prevalence of asthma in a number of occupational categories and subcategories with no evidence of increased risks for women in the same occupations. Our study adds to sparse evidence on occupations with an increased prevalence of self-reported asthma in adult working population in India and also illustrates that the influence of gender should not be overlooked in occupational health research. Occupational asthma is also widely underrecognized by employers, employees and healthcare professionals. Raising awareness among working population that this is an almost entirely a preventable disease would be a major step in reducing its incidence especially in low-and middle-income countries.
What is the key question: Occupational asthma remains relatively under-recognized in India with little or no information regarding preventable causes. What is the bottom line: No previous studies reported occupations with increased prevalence for asthma in India in a nationally representative population, more specifically among women workers. Why read on: This large population-based nationally representative study has confirmed findings from high income countries showing high prevalence of asthma in men in a number of occupation categories and subcategories; however, with no evidence of increased risks for women in the same occupations.
Our study adds to the currently sparse evidence on occupations with an increased odd of asthma in adults in India, but did not identify higher odds of asthma among persons working in high-risk occupations. Table A1. List of occupational categories given in the NFHS-3 data; coded with corresponding NCO codes.

NCO2004 codes
Occupation categories

Legislators, senior officials and managers 111
Elected and legislative officials 112 Administrative and executive officials government and local