Farm operators would entertain multiple strategies for coping with labor procurement problems that may develop in the future. Their strongest inclinations are to adopt technological changes that substitute for labor input, and to step up their recruitment efforts . Smaller majorities of respondents say that they would also consider offering better terms of employment, lowering selection standards, and contracting more with FLCs or custom harvesters. One-third would look to shift their enterprise mix toward less labor-intensive’ crops, and more than a quarter to leave farm business altogether.Until the wave of studies on workers sparked by the 1986 immigration reform law, it was often lamented that too little was known about the hired farm workforce. There was then, and there has continued to be, even less known about how that workforce is managed. Influenced by legal, technological, market, and other contextual factors, farm labor management includes several types of decisions that in tum have direct consequences for agricultural businesses and workers. This study has attempted to analytically describe the different means by which people are brought to and dealt with on farms, to map management practices as they currently are, not to speculate on their adequacy from economic or public policy perspectives. Information from our survey provides for beller understanding of labor management across the range of California fam1s–and of the farms themselves. Though data from any self-administered questionnaire are to be interpreted with caution, these findings clearly tell of a complex industry comprised of diverse production firms and relationships among them. The structure of production agriculture embodies not only vertically integrated producer-marketers but also networks of more specialized, interdependent entities. These entities join efforts through temporary contracts, accomplishing a functional coordination that others pursue through relatively fixed roles and rules in a single organization. California farms exhibit as much variety in their organizational and management characteristics as in their products. Common to all is reliance on the work of people–more than a million different individuals who perform agricultural work some time during the year. While many farm operators intimately link their businesses with family and life style, most depend on people outside the family circle.

Only six percent of all year-round workers on farms, and two percent of the yearly peak workforce, are members of an operator’s family. The labor of non-family workers, who are responsible for the bulk of commodity production in this state, is one of the essential inputs that farmers may procure from external suppliers and contractors. Farmers obtain a large amount of non-employee labor through farm labor contractors , and pest control operators. Two-thirds of all workers on farms are direct farm employees, more or less in particular crop and business size sectors. But three of five farm businesses in the survey also used at least one FLC or CH In 1992. The shares of total labor obtamed from outside providers have increased since 1986. when directly employed workers were 72 percent of all at peak. Farm operators do not sort neatly into groups of either direct employers or labor service customers. Because engaging workers through both employment and contract is the norm, attempts to distinguish farms that hire directly from those that obtain labor in other ways are not likely to be illuminating. There are functions served in procuring labor by either means. The widespread use of contractors notwithstanding, most workers on farms are in fact employees on the payroll, and they are managed in styles that run from the very casual to the systematic. Structure in the personnel function–the extent to which labor management policies, responsibilities, and processes are clearly rationalized–is usually greater in large farm businesses. A bigger scale of operation makes more economical as well as necessary the employment of personnel staff specialists to facilitate hiring, developing, and keeping productive workers. Larger operators in the survey more commonly utilize in-house or external professionals to assist in managing human resources. They tend more to obtain information on prospective employees through written applications and medical exams; to communicate through employee handbooks. written job descriptions and work rules, staff meetings, and regular performance evaluations; to directly employ bilingual supervisors; and to offer non-mandatory fringe benefits. They also verify more carefully the legitimacy of FLCs with whom they do business. And they get audited more by regulatory agencies. Larger farms have assisted more of their formerly undocumented workers through !RCA legalization processes, and they have retained these employees from 1986 to 1992 at higher rates than smaller firms. More generally within a gi\’en commodity sector, employment stability and structured personnel management appear to better reinforce one other in larger farm businesses, particularly those which have geographic or crop diversity that softens net seasonal swings in the need for labor.

Employees are more likely to work year-round in large operations, and, on the whole, year-round farm employees are better compensated, receive more fringe benefits, and have more job security than their seasonal counterparts. Many farms preserve job stability for a core of employees by keeping their organizations lean and contracting for FLC or CH crews to meet additional necds during periods of high activity. This stabilization strategy. however, may effectively define or perpetuate the division between two tiers in the farm workforce. Sometimes juxtaposed in adjoining fields are crews from both tiers harvesting for the very same company label but under quite different terms of employment. Where FLCs are able to hold their operating expenses below those that farmers would incur for their own hires, they can offer customers a current cost advantage over direct employment. Even where they cannot, contractors are appealing to farmers who want to reduce their employment transactions, communication problems, legal liabilities, and technical difficulties in managing personnel. The total need for labor in California agriculture fluctuates over the course of a year, and in most crop sectors the work activity at a given farm swings with the seasons more sharply than in the statewide aggregate. Peak employment in an average farm business is more than three times the year-round level,rolling greenhouse benches and the number of different people employed some time during a year is half again the number present at peak activity. Administrative costs accompany every addition to and deletion from the farm payroll, and personnel transactions would be more numerous yet if not for outside service providers. It is not surprising that FLC employees make up almost twice as much of the peak as of the year-round workforce. The unpredictability of staffing for tasks that depend on weather and biological phenomena magnifies the value of “just-in-time” delivery of labor.Even a most disciplined farmer cannot be confident about seasonal employment plans far in advance, Employing a larger workforce than needed in off-peak periods, to avoid cyclical layoffs and recalls, makes labor expense more of a fixed overhead than a variable operating cost. Arranging for contractors to mobilize people and equipment when needed, in contrast, can help tic labor expense more closely to actual task accomplishment while keeping direct employment lean and stable. Contractual arrangements for labor thus may also enhance longer run flexibility to alter future production, technology, staffing, and terms of employment within the farm business. Cultural and language differences between farm operators and workers compound the challenges of direct recruitment, selection, supervision, instruction, and other job-related communication. More than one-third of farmers cannot communicate directly in the language understood by most of their production employees, usually Spanish, and another third have limited fluency. Finally, it is most difficult for agricultural managers to procure labor from capable workers and stay within all legal guidelines without getting overwhelmed by mandates, prohibitions, and reports.

Although growers and contractors may be deemed jointly liable for violations of some employee protections, farmers reduce or eliminate exposure to claims of wrongdoing by using contract labor. Alter two decades of legislation narrowing gaps between employee protections in the agricultural and non-farm sectors, farmers arc subject to pretty much the same liabilities and constraints as employers in other industries. Judicial decisions giving employees more legal rights within their jobs have also raised the costs and risks of maintaining a directly hired workforce. Increased regulatory complexity and the paperwork associated with agricultural employment in particular have added to reasons for contracting out tasks. The eligibility verification and nondiscrimination provisions of !RCA are only two of many bases for charges that agencies or workers may level against farm employers. Thus, there are practical business considerations behind the use of labor contractors and outside service providers that may include but do not hinge on the 1986 immigration reform. In broad terms, growers patronize contractors to get work done when needed by people who can do it without presenting undue complications. Finding and dealing with contractors, however, can involve other complications that farmers weigh against the burdens of hiring and managing their own employees.Streams of immigrants have been boosting the supply of labor available to California farms for more than one hundred years, but labor procurement is not and will not be merely a matter of numbers. Neither farm jobs nor farm workers are an undifferentiated mass. Even as the post-!RCA labor glut was developing, farmers had trouble filling jobs, and most now arc at least somewhat concerned about finding enough workers with the right qualifications to meet their operiltional needs in the future. Regardless of how many people Me looking for employment, farm operators may have trouble engaging workers with skills that arc suited to emerging and future technologies. Patterns of demand for agricultural labor will undoubtedly be different by the end of this decade. Technological innovations that change farm jobs will hilve effects on who porforn1s them and how these workers are managed. While production systems may retain their basic characters, the context if not the content of virtually every agricultural job will be altered somewhat before the 21st century. Mechanization in the past has been designed to achieve a variety of private and social benefits, such as improved crop quality, more efficient use of fertilizers and pesticides, reduced worker exposure to hazards, preservation of environmental quality, and conservation of water and energy. Whether or not explicitly intended, an increase in labor productivity–or a decrease in the number of people needed to produce a given output–usually has accompanied the other benefits of such change.

As with all case–control studies, selection bias in the recruitment of controls is a potential concern. In this study, a systematic procedure for recruitment of all controls from inpatient and outpatient departments of MTH was used, and only one potential control refused to participate. Because most cases were recruited from the RTC, and all controls from MTH, the catchment areas for MTH and RTC might have been different. RTC patients came from a broader area, because it is a referral center for the western development region of Nepal. A higher proportion of cases than controls were from five districts other than Kaski. The Kaski district includes Pokhara city, and in general, Kaski residents are more likely to live in urban areas and to be wealthier. This could simply mean that living outside of Kaski is associated with higher exposure to TB risk factors but, alternatively, could indicate some selection bias. We adjusted for area of residence in the final model, but this would not necessarily have eliminated such a bias. Another possible source of selection bias arises because we did not exclude some other, non-TB respiratory disease cases from the control group. Unfortunately, control diagnoses were not collected at the time of the study and proved impossible to obtain in retrospect, because of the limited period for which the hospital retains patient records. Because absence of TB was confirmed in controls by X-rays, we can, however, be confident that no chronic obstructive pulmonary disease or pneumonia cases were among our controls. It is possible that inclusion of respiratory disease cases among the controls could have produced a bias toward the null, if risk factors for those cases were similar to risk factors for TB. Information bias may take the form of outcome mis-classification or exposure mis-classification. Because all cases were newly diagnosed with active pulmonary TB on the basis of evidence from clinical tests, and controls were also confirmed by chest X-ray and on-the-spot sputum smear testing as not having active pulmonary TB, we consider that disease mis-classification is unlikely to have occurred.

We obtained all the exposure data by questionnaire. Case–control studies are often considered susceptible to recall bias, in that cases may be more likely than controls to remember past exposures. Because questions asked in this study were about common exposures, however, which both cases and controls experience on a day-to-day basis, we expect recall to have been accurate and any differential recall to have been minimal. We verified the high level of accuracy of reporting of two key exposure variables by visiting the homes of 28 study participants. Considering this, and that there is no prevailing belief that indoor smoke exposure from biomass-burning stoves or kerosene-burning stoves or lamps is related to TB occurrence, we believe exposure misclassification is likely to be minimal. One possible limitation, however, is that we only asked about the main cooking fuel used. This might have led to some misclassification of exposure status. The third main area of potential bias is confounding. We collected data on a much more comprehensive range of exposures than did previous studies and investigated their potential to confound the associations with fuel use. Although confounding was present, adjustment with these variables did not eliminate the key associations. There may, of course, be some residual confounding due to mis-specification of the variables, and there is no way to rule out the possibility of unknown confounding factors causing the associations found. One possibility is malnutrition, for which we obtained no data and which is a known risk factor for TB. However, family income, for which we did obtain data and which is an excellent indicator of a family’s ability to feed itself, was taken into account. A notable finding in our study was the association with biomass used as a heating fuel. This was unexpected because the study design focused on cooking-fuel use. Hence, the study population was limited to women, who generally do the cooking in Nepal. Although we collected data on history of stove and cooking fuel use, we did not collect a comparable level of data for heating fuels and so are unable to examine heating-fuel use for evidence of an exposure–response relationship.

In hindsight, the findings with biomass as a heating and a cooking fuel make sense. Women may light a cooking fire, set the pot atop it, and leave the room, returning only periodically while cooking takes place. On the other hand, use of heating fuel involves minimization of ventilation and deliberate exposure,commercial drying racks as the family sits around the fire. In tropical India and Africa, where several of the other TB and biomass studies have been carried out, use of heating fuel is less common than in the mid-hills of Nepal, where nighttime and winter temperatures are lower. Our study also found the OR for TB to be high among both kerosene stove and lamp users, particularly the latter. Kerosene cooking fuel and kerosene lamp users were for the most part mutually exclusive groups. Only one of the 22 kerosene lamp users in the study used a kerosene stove. Kerosene stove users were more likely to use electricity for lighting. With one exception, as far as we are aware, no previous studies have examined a relationship between kerosene and TB . This one study, carried out in Mexico, obtained crude ORs for use of kerosene-burning stoves of 1.9 for active TB and 4.4 for past TB; no adjusted estimates were presented. We have been unable to find any studies where the relationship between kerosene lighting and TB has been investigated or even incidentally reported. The question arises as to why kerosene as a cooking fuel could be a TB risk factor but not biomass cooking fuel. This could have something to do with the nature of the emissions. Biomass burning produces very obvious smoke, which may irritate the eyes and respiratory tract, encouraging avoidance behavior. Kerosene, on the other hand, has the appearance of burning more cleanly, even if it does produce substantial amounts of fine particulate matter and vapor-phase chemicals, and may not encourage the same avoidance behavior as biomass smoke.There are also likely to be differences in the toxic effects of the pollutant mixtures from the two fuels. Kerosene is one of the main sources of cooking fuel in urban areas and lighting fuel in rural areas of developing countries, including Nepal. Therefore, if kerosene burning can be confirmed as a TB risk factor in other studies, the public health implications would be substantial. In rural areas not connected with electric power, kerosene wick lamps are burned at least 4–5 hr every day. Commonly, these lamps are homemade devices that are highly energy inefficient, with low luminosity. Simple wick kerosene lamps emit substantial amounts of smoke and particles . A study conducted in rural Malawi has shown a higher loading of particulates in alveolar macrophages in men from exposure to kerosene in lamps compared with candles, hurricane lamps, and electric lamps . Other emissions from kerosene combustion include carbon monoxide, carbon dioxide, sulfur dioxide, nitrogen dioxide, formaldehyde, and various VOCs .

An indoor air pollution study conducted in Bangladesh slums has shown significantly higher concentrations of benzene, toluene, xylene, hexane, and total VOCs emitted from kerosene stoves than from wood burning stoves . The use of kerosene fuel is associated with harmful effects that have been documented in a few studies. These effects include impairment of ventilatory function and a rise in blood carboxyhemoglobin in women exposed to kerosene fuel smoke , and a higher incidence of acute lower respiratory infection in children in homes using KFS and BFS . A causal relationship between exposure to biomass fuel smoke and TB is biologically plausible. The smoke could affect either risk of infection or risk of disease in infected people, or both, as has been shown to be the case with tobacco smoking . Without knowledge of the time of infection, however, the present study cannot distinguish between the two possibilities. Inhalation of respirable particles and chemicals found in smoke from these sources generates an inflammatory response and impairs the normal clearance of secretions on the tracheobronchial mucosal surface, and may allow TB bacteria to escape the first level of host defenses, which prevent bacilli from reaching the alveoli . Smoke also impairs the function of pulmonary alveolar macrophages, an important early defense mechanism against bacteria . Alveolar macrophages isolated from the lungs of smokers have reduced phagocytic ability compared with macrophages from nonsmokers and secrete a lower level of proinflammatory cytokines . Exposure to wood smoke in rabbits has been shown to negatively affect antibacterial properties of alveolar macrophages, such as their ability to phagocytize bacteria .Pyrethrum spray collections were conducted monthly in 30 randomly selected sentinel houses in each village from January 2012 to June 2014. Mapping of the location of the houses around the study region was done by the global positioning system and the geographical coordinates recorded. The number of people sleeping in each house was recorded during mosquito sampling. Mosquitoes collected were morphologically identified as An. gambiae s.l. or Anopheles funestus. Legs and wings of the female An. gambiae s.l. were frozen at −20°C in labelled vials before molecular identification by PCR into An. gambiae s.s. or An. arabiensis according to Scott et al.. The head and thorax of the mosquitoes were separated from the abdomen and sporozoite ELISA was used to determine their infectivity with Plasmodium parasites.To determine the mosquito active peak hours during night, rotator traps were set up during the dry season in July–August in 2013 and in the wet season in May–June in 2014. These traps were set both indoors and outdoors in three selected sentinel houses.